Structure and dynamics of a gene network model incorporating small RNAs

As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.

When cost-efficient technologies meet politics:a case study of radical wireless network implementation

Cost efficiency has been a dominant perspective in the traditional IT literature. However, in complex technology and business environment, the widely recognized cost efficient assumption of information technology has been increasingly challenged. Drawing from a case study of wireless network implementation situated in a politically sensitive workplace, this paper provided practice insights for IT managers in today’s networked economy. More specifically, stories experienced in the case study illustrated that despite well-calculated cost efficiency of wireless network infrastructure, the radical implementation process in the case organization encountered enormous challenges and opposition due to the fact that administrators failed to consider various stakeholders’ positions and interests. Eventually, the implementation objectives and outcome were considerably undermined. Implications from this empirical case research reemphasized the significance of understanding political forces situated in any business environment where different stakeholders hold conflicting interests. Lessons learned from the case story further encouraged IT managers and policy makers to better strategize emerging information technology in general and wireless networks in particular as the whole global society and business environment are increasingly facing an emerging wireless world.

Independent modulation of engagement and connectivity of the facial network during affect processing by CACNA1C and ANK3 risk genes for bipolar disorder

IMPORTANCE Genome-wide association studies (GWASs) indicate that single-nucleotide polymorphisms in the CACNA1C and ANK3 genes increase the risk for bipolar disorder (BD). The genes influence neuronal firing by modulating calcium and sodium channel functions, respectively. Both genes modulate ?-aminobutyric acid-transmitting interneuron function and can thus affect brain regional activation and interregional connectivity. OBJECTIVE To determine whether the genetic risk for BD associated with 2 GWAS-supported risk single-nucleotide polymorphisms at CACNA1C rs1006737 and ANK3 rs10994336 is mediated through changes in regional activation and interregional connectivity of the facial affect-processing network. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional functional magnetic resonance imaging study at a research institute of 41 euthymic patients with BD and 46 healthy participants, all of British white descent. MAIN OUTCOMES AND MEASURES Blood oxygen level-dependent signal and effective connectivity measures during the facial affect-processing task. RESULTS In healthy carriers, both genetic risk variants were independently associated with increased regional engagement throughout the facial affect-processing network and increased effective connectivity between the visual and ventral prefrontal cortical regions. In contrast, BD carriers of either genetic risk variant exhibited pronounced reduction in ventral prefrontal cortical activation and visual-prefrontal effective connectivity. CONCLUSIONS AND RELEVANCE Our data demonstrate that the effect of CACNA1C rs1006737 and ANK3 rs10994336 (or genetic variants in linkage disequilibrium) on the brain converges on the neural circuitry involved in affect processing and provides a mechanism linking BD to genome-wide genetic risk variants.

Attachment anxiety and friendship group identification under attachment threat:the moderating role of priming support network expectations

We examined the role of priming participants' own network expectations on their subsequent identification with their friendship group. We examined this prime alongside attachment anxiety and attachment threat, as predictors of friendship group identification. Previous research has suggested that attachment anxiety is associated with negative network expectations. In this study, we extended this work to show that when a network expectation prime was absent, higher attachment anxiety was associated with lower group identification under attachment threat, compared to a control condition. However, when expectations of support network were primed, attachment threat no longer affected group identification, so that only attachment anxiety predicted group identification. This suggests that priming participants who are high in attachment anxiety with their own network expectancies (which are negative), results in participants dis-identifying with their friendship group, regardless of whether or not they have experienced attachment threat. © 2012 Elsevier Ltd.

Reconfiguration of supply chain network:an ISM-based roadmap to performance

Purpose: Short product life cycle and/or mass customization necessitate reconfiguration of operational enablers of supply chain (SC) from time to time in order to harness high levels of performance. The purpose of this paper is to identify the key operational enablers under stochastic environment on which practitioner should focus while reconfiguring a SC network. Design/methodology/approach: The paper used interpretive structural modeling (ISM) approach that presents a hierarchy-based model and the mutual relationships among the enablers. The contextual relationship needed for developing structural self-interaction matrix (SSIM) among various enablers is realized by conducting experiments through simulation of a hypothetical SC network. Findings: The research identifies various operational enablers having a high driving power towards assumed performance measures. In this regard, these enablers require maximum attention and of strategic importance while reconfiguring SC. Practical implications: ISM provides a useful tool to the SC managers to strategically adopt and focus on the key enablers which have comparatively greater potential in enhancing the SC performance under given operational settings. Originality/value: The present research realizes the importance of SC flexibility under the premise of reconfiguration of the operational units in order to harness high value of SC performance. Given the resulting digraph through ISM, the decision maker can focus the key enablers for effective reconfiguration. The study is one of the first efforts that develop contextual relations among operational enablers for SSIM matrix through integration of discrete event simulation to ISM. © Emerald Group Publishing Limited.

The Matrix Method of Determining the Fault Tolerance Degree of a Computer Network Topology

This work presents a theoretical-graph method of determining the fault tolerance degree of the computer network interconnections and nodes. Experimental results received from simulations of this method over a distributed computing network environment are also presented.

Numerical analysis of artificial neural network and volterra-based nonlinear equalizers for coherent optical OFDM

One major drawback of coherent optical orthogonal frequency-division multiplexing (CO-OFDM) that hitherto remains unsolved is its vulnerability to nonlinear fiber effects due to its high peak-to-average power ratio. Several digital signal processing techniques have been investigated for the compensation of fiber nonlinearities, e.g., digital back-propagation, nonlinear pre- and post-compensation and nonlinear equalizers (NLEs) based on the inverse Volterra-series transfer function (IVSTF). Alternatively, nonlinearities can be mitigated using nonlinear decision classifiers such as artificial neural networks (ANNs) based on a multilayer perceptron. In this paper, ANN-NLE is presented for a 16QAM CO-OFDM system. The capability of the proposed approach to compensate the fiber nonlinearities is numerically demonstrated for up to 100-Gb/s and over 1000km and compared to the benchmark IVSTF-NLE. Results show that in terms of Q-factor, for 100-Gb/s at 1000km of transmission, ANN-NLE outperforms linear equalization and IVSTF-NLE by 3.2dB and 1dB, respectively.

The PHAR-QA project: competency framework for pharmacy practice—first steps, the results of the European Network Delphi round 1

PHAR-QA, funded by the European Commission, is producing a framework of competences for pharmacy practice. The framework is in line with the EU directive on sectoral professions and takes into account the diversity of the pharmacy profession and the on-going changes in healthcare systems (with an increasingly important role for pharmacists), and in the pharmaceutical industry. PHAR-QA is asking academia, students and practicing pharmacists to rank competences required for practice. The results show that competences in the areas of drug interactions, need for drug treatment and provision of information and service were ranked highest whereas those in the areas of ability to design and conduct research and development and production of medicines were ranked lower. For the latter two categories, industrial pharmacists ranked them higher than did the other five groups

Improved methodology to evaluate fracture properties of warm-mix asphalt using overlay test

This study developed a reliable and repeatable methodology to evaluate the fracture properties of asphalt mixtures with an overlay test (OT). In the proposed methodology, first, a two-step OT protocol was used to characterize the undamaged and damaged behaviors of asphalt mixtures. Second, a new methodology combining the mechanical analysis of viscoelastic force equilibrium in the OT specimen and finite element simulations was used to determine the undamaged properties and crack growth function of asphalt mixtures. Third, a modified Paris's law replacing the stress intensity factor by the pseudo J-integral was employed to characterize the fracture behavior of asphalt mixtures. Theoretical equations were derived to calculate the parameters A and n (defined as the fracture properties) in the modified Paris's law. The study used a detailed example to calculate A and n from the OT data. The proposed methodology was successfully applied to evaluate the impact of warm-mix asphalt (WMA) technologies on fracture properties. The results of the tested specimens showed that Evotherm WMA technology slightly improved the cracking resistance of asphalt mixtures, while foaming WMA technology provided comparable fracture properties. In addition, the study found that A decreased with the increase in n in general. A linear relationship between 2log(A) and n was established.

A tudásérték meghatározása minőségügyi szempontból, hálózatelemzési módszerekkel (The knowledge value in terms of quality with network analysis methods)

A minőségügy egyik kulcsfeladata, hogy azonosítsa az értékteremtés szempontjából kritikus tényezőket, meghatározza ezek értékét, valamint intézkedjen negatív hatásuk megelőzése és csökkentése érdekében. Az értékteremtés sok esetben folyamatokon keresztül történik, amelyek tevékenységekből, elvégzendő feladatokból állnak. Ezekhez megfelelő munkatársak kellenek, akiknek az egyik legfontosabb jellemzője az általuk birtokolt tudás. Mindezek alapján a feladat-tudás-erőforrás kapcsolatrendszer ismerete és kezelése minőségügyi feladat is. A komplex rendszerek elemzésével foglalkozó hálózatkutatás eszközt biztosíthat ehhez, ezért indokolt a minőségügyi területen történő alkalmazhatóságának vizsgálata. Az alkalmazási lehetőségek rendszerezése érdekében a szerzők kategorizálták a minőségügyi hálózatokat az élek (kapcsolatok) és a csúcsok (hálózati pontok) típusai alapján. Ezt követően definiálták a multimodális (több különböző csúcstípusból álló) tudáshálózatot, amely a feladatokból, az erőforrásokból, a tudáselemekből és a közöttük lévő kapcsolatokból épül fel. A hálózat segítségével kategóriákba sorolták a tudáselemeket, valamint a fokszámok alapján meghatározták értéküket. A multimodális hálózatból képzett tudáselem-hálózatban megadták az összefüggő csoportok jelentését, majd megfogalmaztak egy összefüggést a tudáselem-elvesztés kockázatának meghatározására. _______ The aims of quality management are to identify those factors that have significant influence on value production, qualify or quantify them, and make preventive and corrective actions in order to reduce their negative effects. The core elements of value production are processes and tasks, along with workforce having the necessary knowledge to work. For that reason the task-resource-knowledge structure is pertinent to quality management. Network science provides methods to analyze complex systems; therefore it seems reasonable to study the use of tools of network analysis in association with quality management issues. First of all the authors categorized quality networks according to the types of nodes (vertices) and links (edges or arcs). Focusing on knowledge management, they defined the multimodal knowledge network, consisting of tasks, resources, knowledge items and their interconnections. Based on their degree, network nodes can be categorized and their value can be quantified. Derived from the multimodal network knowledge-item network is to be created, where the meaning of cohesive subgroups is defined. Eventually they proposed a formula for determining the risk of knowledge loss.

Against small arms: An analysis of an international network

Small Arms and Light Weapons (SALW) proliferation was undertaken by the Non-Governmental Organizations (NGOs) as the next important issue in international relations after the success of the International Campaign to Ban Landmines (ICBL). This dissertation focuses on the reasons why the issue of SALW resulted in an Action Program rather than an international convention. Thus, this result was considered as unsuccessful by the advocates of regulating the illicit trade in SALW. The study provides a social movement theoretical approach, using framing, political opportunity and network analysis to explain why the advocates of regulating the illicit trade in SALW did no succeed in their goals. The UN is taken as the arena in which NGOs, States and International Governmental Organizations (IGOs) discussed the illicit trade in SALW. ^ The findings of the study indicate that the political opportunity for the issue of SALW was not ideal. The network of NGOs, States and IGOs was not strong. The NGOs advocating regulation of SALW were divided over the approach of the issue and were part of different coalitions with differing objectives. Despite initial widespread interest among States, only a couple of States were fully committed to the issue till the end. The regional IGOs approached the issue based on their regional priorities and were less interested in an international covenant. The advocates of regulating illicit trade in SALW attempted to frame SALW as a humanitarian issue rather than as a security issue. Thus they were not able to use frame alignment to convince states to treat SALW as a humanitarian issue. In conclusion it can be said that all three items, framing, political opportunity and the network, play a role in the lack of success of advocates for regulating the illicit trade in SALW. ^

Learning Meta-Descriptions of the FOAF Network

Postprint

Experimental comparison of artificial neural network and volterra based nonlinear equalization for CO-OFDM

A novel artificial neural network (ANN)-based nonlinear equalizer (NLE) of low complexity is demonstrated for 40-Gb/s CO-OFDM at 2000 km, revealing ∼1.5 dB enhancement in Q-factor compared to inverse Volterra-series transfer function based NLE.