Spatial Tiling and Streaming in an Immersive Media Delivery Network

NARCIS (Netherlands)

Niamut, O.A.; Prins, M.J.; Brandenburg, R. van; Havekes, A.

2011-01-01

Within the EU FP7 project FascinatE, a capture, production and delivery system capable of supporting pan/tilt/zoom interaction with immersive media is being developed. Intelligent networks with processing components are needed to repurpose the content to suit different device types and framing

A Community-Based Event Delivery Protocol in Publish/Subscribe Systems for Delay Tolerant Sensor Networks

Directory of Open Access Journals (Sweden)

Haigang Gong

2009-09-01

Full Text Available The basic operation of a Delay Tolerant Sensor Network (DTSN is to finish pervasive data gathering in networks with intermittent connectivity, while the publish/subscribe (Pub/Sub for short paradigm is used to deliver events from a source to interested clients in an asynchronous way. Recently, extension of Pub/Sub systems in DTSNs has become a promising research topic. However, due to the unique frequent partitioning characteristic of DTSNs, extension of a Pub/Sub system in a DTSN is a considerably difficult and challenging problem, and there are no good solutions to this problem in published works. To ad apt Pub/Sub systems to DTSNs, we propose CED, a community-based event delivery protocol. In our design, event delivery is based on several unchanged communities, which are formed by sensor nodes in the network according to their connectivity. CED consists of two components: event delivery and queue management. In event delivery, events in a community are delivered to mobile subscribers once a subscriber comes into the community, for improving the data delivery ratio. The queue management employs both the event successful delivery time and the event survival time to decide whether an event should be delivered or dropped for minimizing the transmission overhead. The effectiveness of CED is demonstrated through comprehensive simulation studies.

Drawbacks and benefits associated with inter-organizational collaboration along the discovery-development-delivery continuum: a cancer research network case study.

Science.gov (United States)

Harris, Jenine K; Provan, Keith G; Johnson, Kimberly J; Leischow, Scott J

2012-07-25

The scientific process around cancer research begins with scientific discovery, followed by development of interventions, and finally delivery of needed interventions to people with cancer. Numerous studies have identified substantial gaps between discovery and delivery in health research. Team science has been identified as a possible solution for closing the discovery to delivery gap; however, little is known about effective ways of collaborating within teams and across organizations. The purpose of this study was to determine benefits and drawbacks associated with organizational collaboration across the discovery-development-delivery research continuum. Representatives of organizations working on cancer research across a state answered a survey about how they collaborated with other cancer research organizations in the state and what benefits and drawbacks they experienced while collaborating. We used exponential random graph modeling to determine the association between these benefits and drawbacks and the presence of a collaboration tie between any two network members. Different drawbacks and benefits were associated with discovery, development, and delivery collaborations. The only consistent association across all three was with the drawback of difficulty due to geographic differences, which was negatively associated with collaboration, indicating that those organizations that had collaborated were less likely to perceive a barrier related to geography. The benefit, enhanced access to other knowledge, was positive and significant in the development and delivery networks, indicating that collaborating organizations viewed improved knowledge exchange as a benefit of collaboration. 'Acquisition of additional funding or other resources' and 'development of new tools and methods' were negatively significantly related to collaboration in these networks. So, although improved knowledge access was an outcome of collaboration, more tangible outcomes were not being

Microneedles: quick and easy delivery methods of vaccines

Science.gov (United States)

2017-01-01

Vaccination is the most efficient method for infectious disease prevention. Parenteral injections such as intramuscular, intradermal, and subcutaneous injections have several advantages in vaccine delivery, but there are many drawbacks. Thus, the development of a new vaccine delivery system has long been required. Recently, microneedles have been attracting attention as new vaccination tools. Microneedle is a highly effective transdermal vaccine delivery method due to its mechanism of action, painlessness, and ease of use. Here, we summarized the characteristics of microneedles and the possibilities as a new vaccine delivery route. PMID:28775980

Optimization of a truck-drone in tandem delivery network using k-means and genetic algorithm

Directory of Open Access Journals (Sweden)

Sergio Mourelo Ferrandez

2016-04-01

Full Text Available Purpose: The purpose of this paper is to investigate the effectiveness of implementing unmanned aerial delivery vehicles in delivery networks. We investigate the notion of the reduced overall delivery time, energy, and costs for a truck-drone network by comparing the in-tandem system with a stand-alone delivery effort. The objectives are (1 to investigate the time, energy, and costs associated to a truck-drone delivery network compared to standalone truck or drone, (2 to propose an optimization algorithm that determines the optimal number of launch sites and locations given delivery requirements, and drones per truck, (3 to develop mathematical formulations for closed form estimations for the optimal number of launch locations, optimal total time, as well as the associated cost for the system. Design/methodology/approach: The design of the algorithm herein computes the minimal time of delivery utilizing K-means clustering to find launch locations, as well as a genetic algorithm to solve the truck route as a traveling salesmen problem (TSP. The optimal solution is determined by finding the minimum cost associated to the parabolic convex cost function. The optimal min-cost is determined by finding the most efficient launch locations using K-means algorithms to determine launch locations and a genetic algorithm to determine truck route between those launch locations.  Findings: Results show improvements with in-tandem delivery efforts as opposed to standalone systems. Further, multiple drones per truck are more optimal and contribute to savings in both energy and time. For this, we sampled various initialization variables to derive closed form mathematical solutions for the problem. Originality/value: Ultimately, this provides the necessary analysis of an integrated truck-drone delivery system which could be implemented by a company in order to maximize deliveries while minimizing time and energy. Closed-form mathematical solutions can be used as

TRANSDERMAL DRUG DELIVERY AND METHODS TO ENHANCE IT

Directory of Open Access Journals (Sweden)

E. G. Kuznetsova

2016-01-01

Full Text Available The paper presents the common methods employed in recent years for enhancing transdermal delivery of drug substances when applying transdermal therapeutic delivery systems. The chemical, physical and mechanical methods to enhance the transport of macromolecular compounds through the skin are considered in details. 

Renewable energy delivery systems and methods

Science.gov (United States)

Walker, Howard Andrew

2013-12-10

A system, method and/or apparatus for the delivery of energy at a site, at least a portion of the energy being delivered by at least one or more of a plurality of renewable energy technologies, the system and method including calculating the load required by the site for the period; calculating the amount of renewable energy for the period, including obtaining a capacity and a percentage of the period for the renewable energy to be delivered; comparing the total load to the renewable energy available; and, implementing one or both of additional and alternative renewable energy sources for delivery of energy to the site.

Software Delivery Risk Management: Application of Bayesian Networks in Agile Software Development

Directory of Open Access Journals (Sweden)

Ancveire Ieva

2015-12-01

Full Text Available The information technology industry cannot be imagined without large- or small-scale projects. They are implemented to develop systems enabling key business processes and improving performance and enterprise resource management. However, projects often experience various difficulties during their execution. These problems are usually related to the three objectives of the project – costs, quality and deadline. A way these challenges can be solved is project risk management. However, not always the main problems and their influencing factors can be easily identified. Usually there is a need for a more profound analysis of the problem situation. In this paper, we propose the use of a Bayesian Network concept for quantitative risk management in agile projects. The Bayesian Network is explored using a case study focusing on a project that faces difficulties during the software delivery process. We explain why an agile risk analysis is needed and assess the potential risk factors, which may occur during the project. Thereafter, we design the Bayesian Network to capture the actual problem situation and make suggestions how to improve the delivery process based on the measures to be taken to reduce the occurrence of project risks.

Rural and urban women entrepreneurs: A comparison of service needs and delivery methods priorities

Directory of Open Access Journals (Sweden)

Davis, A.

2011-01-01

Full Text Available Women entrepreneurs face a wide variety of barriers and challenges throughout the life and growth of their entrepreneurial venture. This study expands the knowledge base on women entrepreneurs’ needs, specifically their needs in terms of service areas and service delivery method preferences. Twenty three “needed” service areas were identified by 95 Manitoba based women entrepreneurs. The first five included: finding new customers, growth benefits and tools, market expansion, general marketing, and networking skills. This study also examined the differences between urban and rural based entrepreneurs. Two service need areas “how to find mentors and role models” and “legal issues” exhibited statistically significant priority differences. Service delivery methods did not produce any statistically significant differences. Overall, this study concludes that regardless of location, women entrepreneurs’ training and support needs are not significantly that different. The effects of entrepreneurial stage and years in business on entrepreneurial support needs are also examined.

Fault Activity Aware Service Delivery in Wireless Sensor Networks for Smart Cities

Directory of Open Access Journals (Sweden)

Xiaomei Zhang

2017-01-01

Full Text Available Wireless sensor networks (WSNs are increasingly used in smart cities which involve multiple city services having quality of service (QoS requirements. When misbehaving devices exist, the performance of current delivery protocols degrades significantly. Nonetheless, the majority of existing schemes either ignore the faulty behaviors’ variability and time-variance in city environments or focus on homogeneous traffic for traditional data services (simple text messages rather than city services (health care units, traffic monitors, and video surveillance. We consider the problem of fault-aware multiservice delivery, in which the network performs secure routing and rate control in terms of fault activity dynamic metric. To this end, we first design a distributed framework to estimate the fault activity information based on the effects of nondeterministic faulty behaviors and to incorporate these estimates into the service delivery. Then we present a fault activity geographic opportunistic routing (FAGOR algorithm addressing a wide range of misbehaviors. We develop a leaky-hop model and design a fault activity rate-control algorithm for heterogeneous traffic to allocate resources, while guaranteeing utility fairness among multiple city services. Finally, we demonstrate the significant performance of our scheme in routing performance, effective utility, and utility fairness in the presence of misbehaving sensors through extensive simulations.

Feature Extraction Method for High Impedance Ground Fault Localization in Radial Power Distribution Networks

DEFF Research Database (Denmark)

Jensen, Kåre Jean; Munk, Steen M.; Sørensen, John Aasted

1998-01-01

A new approach to the localization of high impedance ground faults in compensated radial power distribution networks is presented. The total size of such networks is often very large and a major part of the monitoring of these is carried out manually. The increasing complexity of industrial...... of three phase voltages and currents. The method consists of a feature extractor, based on a grid description of the feeder by impulse responses, and a neural network for ground fault localization. The emphasis of this paper is the feature extractor, and the detection of the time instance of a ground fault...... processes and communication systems lead to demands for improved monitoring of power distribution networks so that the quality of power delivery can be kept at a controlled level. The ground fault localization method for each feeder in a network is based on the centralized frequency broadband measurement...

Performance analysis of data delivery schemes for a multi-sink wireless sensor network

NARCIS (Netherlands)

Tan, H.P.; Gabor, A.F.; Seah, W.K.G.; Lee, P.W.Q.

2008-01-01

Wireless sensor networks are expected to be deployed in harsh environments characterised by extremely poor and fluctuating channel conditions. With the commonly adopted single-sink architecture, such conditions are exemplified by contention near the sink as a result of multipath delivery. This may

Cyclic delivery scheduling to customers with different priorities

Directory of Open Access Journals (Sweden)

Katarzyna Zofia Gdowska

2013-12-01

Full Text Available Background: In this paper a cyclic delivery scheduling problem for customers with different priorities is presented. Shops, which are provided with deliveries, are occasionally located in places which are crucial for the proper flow of traffic. In such places coordination of deliveries is crucial; therefore it allows to completely eliminate the phenomenon of the simultaneous arrivals of suppliers. Methods: In this paper the cyclic delivery scheduling problem for customers with different priorities was presented. To this theoretical problem a mix integer programming model was developed. Specific approach to the cyclic delivery scheduling problem is inspired by timetabling problem for urban public transport. Results: Mixed integer programming model was employed for solving four cases of cyclic delivery scheduling problem for customers with different priorities. When the value of the synchronization priority assigned to a single customer raised then the total number of synchronizations in the whole network decreased. In order to compare solutions a synchronization rate was utilized. A simple factor was utilized - the proportion of number of synchronizations of deliveries to a given customer to the total number of synchronizations obtained for the whole network. When the value of synchronization priority raised then the value of synchronization rate of this customer improved significantly. Conclusions: The mixed integer programming model for the cyclic delivery scheduling problem for customers with different priorities presented in this paper can be utilized for generating schedules of serving customers located in places where only one delivery can be received and unloaded at one go and where there is no space for other suppliers to wait in a queue. Such a schedule can be very useful for organizing deliveries to small shops united in a franchising network, since they operate in a way that is very similar to the network presented in this paper

Riparian Sediment Delivery Ratio: Stiff Diagrams and Artifical Neural Networks

Science.gov (United States)

Various methods are used to estimate sediment transport through riparian buffers and grass jilters with the sediment delivery ratio having been the most widely applied. The U.S. Forest Service developed a sediment delivery ratio using the stiff diagram and a logistic curve to int...

Customer satisfaction of mobile telecommunication networks in Ghana: service delivery perspective

OpenAIRE

A.R. ABDUL-AZIZ; Bashiru I.I. SAEED; Ayogyam ALEXANDER

2014-01-01

Organizations, both private and public, in today’s dynamic marketplaces are increasingly leaving antiquated marketing philosophies and strategies to the adoption of more customer driven initiatives that seek to understand, attract, retain and build intimate long term relationship with profitable customers. This article analyzed customer satisfaction with the service delivery of mobile telecommunication networks in Ghana using a binary logistic regression model. Primary data was collected thro...

Methods and metrics challenges of delivery-system research

Directory of Open Access Journals (Sweden)

Alexander Jeffrey A

2012-03-01

Full Text Available Abstract Background Many delivery-system interventions are fundamentally about change in social systems (both planned and unplanned. This systems perspective raises a number of methodological challenges for studying the effects of delivery-system change--particularly for answering questions related to whether the change will work under different conditions and how the change is integrated (or not into the operating context of the delivery system. Methods The purpose of this paper is to describe the methodological and measurement challenges posed by five key issues in delivery-system research: (1 modeling intervention context; (2 measuring readiness for change; (3 assessing intervention fidelity and sustainability; (4 assessing complex, multicomponent interventions; and (5 incorporating time in delivery-system models to discuss recommendations for addressing these issues. For each issue, we provide recommendations for how research may be designed and implemented to overcome these challenges. Results and conclusions We suggest that a more refined understanding of the mechanisms underlying delivery-system interventions (treatment theory and the ways in which outcomes for different classes of individuals change over time are fundamental starting points for capturing the heterogeneity in samples of individuals exposed to delivery-system interventions. To support the research recommendations outlined in this paper and to advance understanding of the "why" and "how" questions of delivery-system change and their effects, funding agencies should consider supporting studies with larger organizational sample sizes; longer duration; and nontraditional, mixed-methods designs. A version of this paper was prepared under contract with the Agency for Healthcare Research and Quality (AHRQ, US Department of Health and Human Services for presentation and discussion at a meeting on "The Challenge and Promise of Delivery System Research," held in Sterling, VA, on

A new electrospray method for targeted gene delivery.

Science.gov (United States)

Boehringer, Stephan; Ruzgys, Paulius; Tamò, Luca; Šatkauskas, Saulius; Geiser, Thomas; Gazdhar, Amiq; Hradetzky, David

2018-03-05

A challenge for gene therapy is absence of safe and efficient local delivery of therapeutic genetic material. An efficient and reproducible physical method of electrospray for localized and targeted gene delivery is presented. Electrospray works on the principle of coulombs repulsion, under influence of electric field the liquid carrying genetic material is dispersed into micro droplets and is accelerated towards the targeted tissue, acting as a counter electrode. The accelerated droplets penetrate the targeted cells thus facilitating the transfer of genetic material into the cell. The work described here presents the principle of electrospray for gene delivery, the basic instrument design, and the various optimized parameters to enhance gene transfer in vitro. We estimate a transfection efficiency of up to 60% was achieved. We describe an efficient gene transfer method and a potential electrospray-mediated gene transfer mechanism.

NILDE, Network Inter Library Document Exchange: An Italian Document Delivery System

Science.gov (United States)

Brunetti, F.; Gasperini, A.; Mangiaracina, S.

2007-10-01

This poster presents NILDE, a document delivery system supporting the exchange of documents via the internet. The system has been set up by the Central Library of the National Research Council of Bologna (Italy) in order to make use of new internet technology, to promote cooperation between Italian university libraries and research libraries, and to achieve quick response times in satisfying DD requests. The Arcetri Astrophysical Observatory Library was the first astronomical library to join the NILDE project from its earliest days in 2002. Many were the reasons for this choice: automation of the DD processes, security and reliability of the network, creation of usage statistics and reports, reduction of DD System management costs and so on. This work describes the benefits of NILDE and discusses the role of an organized document delivery system as an important tool to cope with the difficult constraints of the publishing market.

Building Service Delivery Networks: Partnership Evolution Among Children's Behavioral Health Agencies in Response to New Funding.

Science.gov (United States)

Bunger, Alicia C; Doogan, Nathan J; Cao, Yiwen

2014-12-01

Meeting the complex needs of youth with behavioral health problems requires a coordinated network of community-based agencies. Although fiscal scarcity or retrenchment can limit coordinated services, munificence can stimulate service delivery partnerships as agencies expand programs, hire staff, and spend more time coordinating services. This study examines the 2-year evolution of referral and staff expertise sharing networks in response to substantial new funding for services within a regional network of children's mental health organizations. Quantitative network survey data were collected from directors of 22 nonprofit organizations that receive funding from a county government-based behavioral health service fund. Both referral and staff expertise sharing networks changed over time, but results of a stochastic actor-oriented model of network dynamics suggest the nature of this change varies for these networks. Agencies with higher numbers of referral and staff expertise sharing partners tend to maintain these ties and/or develop new relationships over the 2 years. Agencies tend to refer to agencies they trust, but trust was not associated with staff expertise sharing ties. However, agencies maintain or form staff expertise sharing ties with referral partners, or with organizations that provide similar services. In addition, agencies tend to reciprocate staff expertise sharing, but not referrals. Findings suggest that during periods of resource munificence and service expansion, behavioral health organizations build service delivery partnerships in complex ways that build upon prior collaborative history and coordinate services among similar types of providers. Referral partnerships can pave the way for future information sharing relationships.

The African Field Epidemiology Network-Networking for effective field epidemiology capacity building and service delivery

Science.gov (United States)

Gitta, Sheba Nakacubo; Mukanga, David; Babirye, Rebecca; Dahlke, Melissa; Tshimanga, Mufuta; Nsubuga, Peter

2011-01-01

Networks are a catalyst for promoting common goals and objectives of their membership. Public Health networks in Africa are crucial, because of the severe resource limitations that nations face in dealing with priority public health problems. For a long time, networks have existed on the continent and globally, but many of these are disease-specific with a narrow scope. The African Field Epidemiology Network (AFENET) is a public health network established in 2005 as a non-profit networking alliance of Field Epidemiology and Laboratory Training Programs (FELTPs) and Field Epidemiology Training Programs (FETPs) in Africa. AFENET is dedicated to helping ministries of health in Africa build strong, effective and sustainable programs and capacity to improve public health systems by partnering with global public health experts. The Network's goal is to strengthen field epidemiology and public health laboratory capacity to contribute effectively to addressing epidemics and other major public health problems in Africa. AFENET currently networks 12 FELTPs and FETPs in sub-Saharan Africa with operations in 20 countries. AFENET has a unique tripartite working relationship with government technocrats from human health and animal sectors, academicians from partner universities, and development partners, presenting the Network with a distinct vantage point. Through the Network, African nations are making strides in strengthening their health systems. Members are able to: leverage resources to support field epidemiology and public health laboratory training and service delivery notably in the area of outbreak investigation and response as well as disease surveillance; by-pass government bureaucracies that often hinder and frustrate development partners; and consolidate efforts of different partners channelled through the FELTPs by networking graduates through alumni associations and calling on them to offer technical support in various public health capacities as the need arises

Solution Method of Multi-Product Two-Stage Logistics Problem with Constraints of Delivery Course

Science.gov (United States)

Ataka, Shinichiro; Gen, Mitsuo

The logistics network design is one of the important phase of Supply Chain Management (SCM) and it is the problem that should be optimized for long-term promotion of efficiency of the whole supply chain. Usually a plant produces different type of products. Even if it is a factory of the same company, delivery is different by a kind of a produced product. The restrictions which this model has are deeply concerned with TP in the real world. In this paper, we consider the logistics network design problems with multi-products and constraints for delivery course. To solve the problem, we used a hybrid priority-based Genetic Algorithm (h-priGA), and we tried the comparison experiment with priority-based Genetic Algorithm (priGA)and h-priGA, we show it about the effectiveness of h-priGA.

Coherent detection passive optical access network enabling converged delivery of broadcast and dedicated broadband services

DEFF Research Database (Denmark)

Osadchiy, Alexey Vladimirovich; Prince, Kamau; Guerrero Gonzalez, Neil

2011-01-01

We propose a passive optical network architecture based on coherent detection for converged delivery of broadcast services from a dedicated remote broadcast server and user-specific services from a local central office. We experimentally demonstrate this architecture with mixed traffic types....... The broadcast channels were transmitted over 78 km of single mode fiber to a central office where they were multiplexed with the unicast channels for further fiber transmission over 34-km to reach the access network. Successful detection of all channels is demonstrated....

Locality-Driven Parallel Static Analysis for Power Delivery Networks

KAUST Repository

Zeng, Zhiyu

2011-06-01

Large VLSI on-chip Power Delivery Networks (PDNs) are challenging to analyze due to the sheer network complexity. In this article, a novel parallel partitioning-based PDN analysis approach is presented. We use the boundary circuit responses of each partition to divide the full grid simulation problem into a set of independent subgrid simulation problems. Instead of solving exact boundary circuit responses, a more efficient scheme is proposed to provide near-exact approximation to the boundary circuit responses by exploiting the spatial locality of the flip-chip-type power grids. This scheme is also used in a block-based iterative error reduction process to achieve fast convergence. Detailed computational cost analysis and performance modeling is carried out to determine the optimal (or near-optimal) number of partitions for parallel implementation. Through the analysis of several large power grids, the proposed approach is shown to have excellent parallel efficiency, fast convergence, and favorable scalability. Our approach can solve a 16-million-node power grid in 18 seconds on an IBM p5-575 processing node with 16 Power5+ processors, which is 18.8X faster than a state-of-the-art direct solver. © 2011 ACM.

Self-reinforcement and protein sustained delivery of hyaluronan hydrogel by tailoring a dually cross-linked network

Energy Technology Data Exchange (ETDEWEB)

Luo, Chunhong; Xu, Guoguang; Wang, Xinghui [Department of Materials Science and Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632 (China); Tu, Mei; Zeng, Rong; Rong, Jianhua [Department of Materials Science and Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632 (China); Engineering Research Center of Artificial Organs and Materials, Ministry of Education, Guangzhou 510632 (China); Zhao, Jianhao, E-mail: jhzhao@jnu.edu.cn [Department of Materials Science and Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632 (China); Engineering Research Center of Artificial Organs and Materials, Ministry of Education, Guangzhou 510632 (China)

2015-01-01

A series of self-reinforcing hyaluronan hydrogels were developed to improve mechanical properties and protein sustained delivery thanks to a dually cross-linked network. Hyaluronan gel particles (HGPs, 1–5 μm in diameter) with different cross-linking densities, i.e. HGPs-1.5, HGPs-3 and HGPs-15, were prepared in an inverse emulsion system and used as the reinforcing phase after glycidyl methacrylation, while glycidyl methacrylated hyaluronan with a substitution degree of 45.2% was synthesized as the matrix phase. These two phases were cross-linked under ultraviolet irradiation to form self-reinforcing hyaluronan hydrogels (srHAs) that showed typical cross-linked structure of HGPs connecting the matrix phase by cross-section observation. In comparison to hyaluronan bulk gels and their blends with HGPs, srHAs distinctly enhanced the mechanical properties and BSA long-term sustained delivery, especially srHA-1.5 showed the highest compressive modulus of 220 ± 15 kPa and the slowest BSA delivery (67% release at 14 d). The 3T3 fibroblast cell culture showed that all the srHAs had no cytotoxicity. - Highlights: • New self-reinforcing HA hydrogels with a dually cross-linked network were developed. • Self-reinforcing HA hydrogels greatly enhanced the mechanical properties. • Self-reinforcing HA hydrogels prolonged the sustained delivery of BSA. • The self-reinforcing mechanism and BSA diffusion mechanism were discussed. • Self-reinforcing HA hydrogels had no cytotoxicity to 3T3 fibroblast cells.

Self-reinforcement and protein sustained delivery of hyaluronan hydrogel by tailoring a dually cross-linked network

International Nuclear Information System (INIS)

Luo, Chunhong; Xu, Guoguang; Wang, Xinghui; Tu, Mei; Zeng, Rong; Rong, Jianhua; Zhao, Jianhao

2015-01-01

A series of self-reinforcing hyaluronan hydrogels were developed to improve mechanical properties and protein sustained delivery thanks to a dually cross-linked network. Hyaluronan gel particles (HGPs, 1–5 μm in diameter) with different cross-linking densities, i.e. HGPs-1.5, HGPs-3 and HGPs-15, were prepared in an inverse emulsion system and used as the reinforcing phase after glycidyl methacrylation, while glycidyl methacrylated hyaluronan with a substitution degree of 45.2% was synthesized as the matrix phase. These two phases were cross-linked under ultraviolet irradiation to form self-reinforcing hyaluronan hydrogels (srHAs) that showed typical cross-linked structure of HGPs connecting the matrix phase by cross-section observation. In comparison to hyaluronan bulk gels and their blends with HGPs, srHAs distinctly enhanced the mechanical properties and BSA long-term sustained delivery, especially srHA-1.5 showed the highest compressive modulus of 220 ± 15 kPa and the slowest BSA delivery (67% release at 14 d). The 3T3 fibroblast cell culture showed that all the srHAs had no cytotoxicity. - Highlights: • New self-reinforcing HA hydrogels with a dually cross-linked network were developed. • Self-reinforcing HA hydrogels greatly enhanced the mechanical properties. • Self-reinforcing HA hydrogels prolonged the sustained delivery of BSA. • The self-reinforcing mechanism and BSA diffusion mechanism were discussed. • Self-reinforcing HA hydrogels had no cytotoxicity to 3T3 fibroblast cells

Design of Drug Delivery Methods for the Brain and Central Nervous System

Science.gov (United States)

Lueshen, Eric

Due to the impermeability of the blood-brain barrier (BBB) to macromolecules delivered systemically, drug delivery to the brain and central nervous system (CNS) is quite difficult and has become an area of intense research. Techniques such as convection-enhanced intraparenchymal delivery and intrathecal magnetic drug targeting offer a means of circumventing the blood-brain barrier for targeted delivery of therapeutics. This dissertation focuses on three aspects of drug delivery: pharmacokinetics, convection-enhanced delivery, and intrathecal magnetic drug targeting. Classical pharmacokinetics mainly uses black-box curve fitting techniques without biochemical or biological basis. This dissertation advances the state-of-the-art of pharmacokinetics and pharmacodynamics by incorporating first principles and biochemical/biotransport mechanisms in the prediction of drug fate in vivo. A whole body physiologically-based pharmacokinetics (PBPK) modeling framework is engineered which creates multiscale mathematical models for entire organisms composed of organs, tissues, and a detailed vasculature network to predict drug bioaccumulation and to rigorously determine kinetic parameters. These models can be specialized to account for species, weight, gender, age, and pathology. Systematic individual therapy design using the proposed mechanistic PBPK modeling framework is also a possibility. Biochemical, anatomical, and physiological scaling laws are also developed to accurately project drug kinetics in humans from small animal experiments. Our promising results demonstrate that the whole-body mechanistic PBPK modeling approach not only elucidates drug mechanisms from a biochemical standpoint, but offers better scaling precision. Better models can substantially accelerate the introduction of drug leads to clinical trials and eventually to the market by offering more understanding of the drug mechanisms, aiding in therapy design, and serving as an accurate dosing tool. Convection

METHOD OF CHOOSING THE TECHNOLOGY OF VEHICLE OPERATION ON DELIVERY ROUTES

Directory of Open Access Journals (Sweden)

Ye. Nagornyi

2014-10-01

Full Text Available A method for determining the technology of vehicles operation on delivery (team routes, which allows to determine the optimal sequence of cargo delivery to customers by vehicles of certain capacity in order to meet the requirements of cargo owners regarding the conditions of service is offered. Recommendations for creation of an automated system of forming the technology of vehicles operation on delivery routes are developed.

Exploring trade-offs between VMAT dose quality and delivery efficiency using a network optimization approach

International Nuclear Information System (INIS)

Salari, Ehsan; Craft, David; Wala, Jeremiah

2012-01-01

To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called vmerge, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. vmerge begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the ‘ideal’ dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard vmerge algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the

Exploring trade-offs between VMAT dose quality and delivery efficiency using a network optimization approach.

Science.gov (United States)

Salari, Ehsan; Wala, Jeremiah; Craft, David

2012-09-07

To formulate and solve the fluence-map merging procedure of the recently-published VMAT treatment-plan optimization method, called VMERGE, as a bi-criteria optimization problem. Using an exact merging method rather than the previously-used heuristic, we are able to better characterize the trade-off between the delivery efficiency and dose quality. VMERGE begins with a solution of the fluence-map optimization problem with 180 equi-spaced beams that yields the 'ideal' dose distribution. Neighboring fluence maps are then successively merged, meaning that they are added together and delivered as a single map. The merging process improves the delivery efficiency at the expense of deviating from the initial high-quality dose distribution. We replace the original merging heuristic by considering the merging problem as a discrete bi-criteria optimization problem with the objectives of maximizing the treatment efficiency and minimizing the deviation from the ideal dose. We formulate this using a network-flow model that represents the merging problem. Since the problem is discrete and thus non-convex, we employ a customized box algorithm to characterize the Pareto frontier. The Pareto frontier is then used as a benchmark to evaluate the performance of the standard VMERGE algorithm as well as two other similar heuristics. We test the exact and heuristic merging approaches on a pancreas and a prostate cancer case. For both cases, the shape of the Pareto frontier suggests that starting from a high-quality plan, we can obtain efficient VMAT plans through merging neighboring fluence maps without substantially deviating from the initial dose distribution. The trade-off curves obtained by the various heuristics are contrasted and shown to all be equally capable of initial plan simplifications, but to deviate in quality for more drastic efficiency improvements. This work presents a network optimization approach to the merging problem. Contrasting the trade-off curves of the merging

Physical non-viral gene delivery methods for tissue engineering.

Science.gov (United States)

Mellott, Adam J; Forrest, M Laird; Detamore, Michael S

2013-03-01

The integration of gene therapy into tissue engineering to control differentiation and direct tissue formation is not a new concept; however, successful delivery of nucleic acids into primary cells, progenitor cells, and stem cells has proven exceptionally challenging. Viral vectors are generally highly effective at delivering nucleic acids to a variety of cell populations, both dividing and non-dividing, yet these viral vectors are marred by significant safety concerns. Non-viral vectors are preferred for gene therapy, despite lower transfection efficiencies, and possess many customizable attributes that are desirable for tissue engineering applications. However, there is no single non-viral gene delivery strategy that "fits-all" cell types and tissues. Thus, there is a compelling opportunity to examine different non-viral vectors, especially physical vectors, and compare their relative degrees of success. This review examines the advantages and disadvantages of physical non-viral methods (i.e., microinjection, ballistic gene delivery, electroporation, sonoporation, laser irradiation, magnetofection, and electric field-induced molecular vibration), with particular attention given to electroporation because of its versatility, with further special emphasis on Nucleofection™. In addition, attributes of cellular character that can be used to improve differentiation strategies are examined for tissue engineering applications. Ultimately, electroporation exhibits a high transfection efficiency in many cell types, which is highly desirable for tissue engineering applications, but electroporation and other physical non-viral gene delivery methods are still limited by poor cell viability. Overcoming the challenge of poor cell viability in highly efficient physical non-viral techniques is the key to using gene delivery to enhance tissue engineering applications.

Physical non-viral gene delivery methods for tissue engineering

Science.gov (United States)

Mellott, Adam J.; Forrest, M. Laird; Detamore, Michael S.

2016-01-01

The integration of gene therapy into tissue engineering to control differentiation and direct tissue formation is not a new concept; however, successful delivery of nucleic acids into primary cells, progenitor cells, and stem cells has proven exceptionally challenging. Viral vectors are generally highly effective at delivering nucleic acids to a variety of cell populations, both dividing and non-dividing, yet these viral vectors are marred by significant safety concerns. Non-viral vectors are preferred for gene therapy, despite lower transfection efficiencies, and possess many customizable attributes that are desirable for tissue engineering applications. However, there is no single non-viral gene delivery strategy that “fits-all” cell types and tissues. Thus, there is a compelling opportunity to examine different non-viral vectors, especially physical vectors, and compare their relative degrees of success. This review examines the advantages and disadvantages of physical non-viral methods (i.e., microinjection, ballistic gene delivery, electroporation, sonoporation, laser irradiation, magnetofection, and electric field-induced molecular vibration), with particular attention given to electroporation because of its versatility, with further special emphasis on Nucleofection™. In addition, attributes of cellular character that can be used to improve differentiation strategies are examined for tissue engineering applications. Ultimately, electroporation exhibits a high transfection efficiency in many cell types, which is highly desirable for tissue engineering applications, but electroporation and other physical non-viral gene delivery methods are still limited by poor cell viability. Overcoming the challenge of poor cell viability in highly efficient physical non-viral techniques is the key to using gene delivery to enhance tissue engineering applications. PMID:23099792

PEG-based degradable networks for drug delivery applications

Science.gov (United States)

Ostroha, Jamie L.

The controlled delivery of therapeutic agents by biodegradable hydrogels has become a popular mechanism for drug administration in recent years. Hydrogels are three-dimensional networks of polymer chains held together by crosslinks. Although the changes which the hydrogel undergoes in solution are important to a wide range of experimental studies, they have not been investigated systematically and the factors which influence the degree of swelling have not been adequately described. Hydrogels made of poly(ethylene glycol) (PEG) will generally resist degradation in aqueous conditions, while a hydrogel made from a copolymer of poly(lactic acid) (PLA) and PEG will degrade via hydrolysis of the lactic acid group. This ability to degrade makes these hydrogels promising candidates for controlled release drug delivery systems. The goal of this research was to characterize the swelling and degradation of both degradable and non-degradable gels and to evaluate the release of different drugs from these hydrogels, where the key variable is the molecular weight of the PEG segment. These hydrogels were formed by the addition and subsequent chemically crosslinking of methacrylate end groups. During crosslinking, both PEG and LA-PEG-LA hydrogels of varied PEG molecular weight were loaded with Vitamin B12, Insulin, Haloperidol, and Dextran. It was shown that increasing PEG molecular weight produces a hydrogel with larger pores, thus increasing water uptake and degradation rate. While many environmental factors do not affect the swelling behavior, they do significantly impact the degradation of the hydrogel, and thus the release of incorporated therapeutic agents.

Can the delivery method influence lower urinary tract symptoms triggered by the first pregnancy?

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Simone Botelho

2012-04-01

Full Text Available INTRODUCTION AND OBJECTIVES: The increase of the intensity of urinary symptoms in late pregnancy and postpartum has been well documented by several authors, but their causes remain uncertain, partly because of its probable multifactor origin. There are also controversies whether the etiology of lower urinary tract symptoms during pregnancy is the same as postpartum and whether the method of delivery could influence the risk of onset of urinary symptoms. This study aimed to evaluate the urinary symptoms triggered during pregnancy and its evolution in the late puerperium, correlating them with the delivery method. MATERIALS AND METHODS: A longitudinal study was conducted, which included 75 primigravidae women, classified according to method of delivery as: (VD vaginal delivery with right mediolateral episiotomy (n = 28; (CS elective caesarean section (n = 26; and (EC emergency caesarean section (n = 21. Urinary symptoms were assessed in the last trimester of pregnancy and at 45 days (± 10 of puerperium with validated versions for Portuguese language of the following questionnaires: International Consultation on Incontinence Questionnaire - Urinary Incontinence Short Form (ICIQ-UI SF and the International Consultation on Incontinence Questionnaire Overactive Bladder (ICIQ-OAB. RESULTS: It was observed that frequency, urgency, nocturia and urge incontinence, triggered during pregnancy, decreased significantly in the postpartum period, regardless of the delivery method (p = 0.0001. However, symptoms related to urinary loss due to stress persisted after vaginal delivery (p = 0.0001. CONCLUSIONS: Urgency, frequency and nocturia triggered during pregnancy tend to disappear in the late postpartum period, regardless of the delivery method, but the symptoms related to urinary loss due to stress tend to persist in late postpartum period after vaginal delivery.

Quantitative Efficiency Evaluation Method for Transportation Networks

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Jin Qin

2014-11-01

Full Text Available An effective evaluation of transportation network efficiency/performance is essential to the establishment of sustainable development in any transportation system. Based on a redefinition of transportation network efficiency, a quantitative efficiency evaluation method for transportation network is proposed, which could reflect the effects of network structure, traffic demands, travel choice, and travel costs on network efficiency. Furthermore, the efficiency-oriented importance measure for network components is presented, which can be used to help engineers identify the critical nodes and links in the network. The numerical examples show that, compared with existing efficiency evaluation methods, the network efficiency value calculated by the method proposed in this paper can portray the real operation situation of the transportation network as well as the effects of main factors on network efficiency. We also find that the network efficiency and the importance values of the network components both are functions of demands and network structure in the transportation network.

A Short-Circuit Method for Networks.

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Ong, P. P.

1983-01-01

Describes a method of network analysis that allows avoidance of Kirchoff's Laws (providing the network is symmetrical) by reduction to simple series/parallel resistances. The method can be extended to symmetrical alternating current, capacitance or inductance if corresponding theorems are used. Symmetric cubic network serves as an example. (JM)

AN APPLICATION FOR EFFICIENT TELECOMMUNICATION NETWORKS PROVISIONING USING LINEAR PROGRAMMING

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Maria Augusta Soares Machado

2015-03-01

Full Text Available This paper presents a practical proposition for the application of the Linear Programming quantitative method in order to assist planning and control of customer circuit delivery activities in telecommunications companies working with the corporative market. Based upon data provided for by a telecom company operating in Brazil, the Linear Programming method was employed for one of the classical problems of determining the optimum mix of production quantities for a set of five products of that company: Private Telephone Network, Internet Network, Intranet Network, Low Speed Data Network, and High Speed Data Network, in face of several limitations of the productive resources, seeking to maximize the company’s monthly revenue. By fitting the production data available into a primary model, observation was made as to what number of monthly activations for each product would be mostly optimized in order to achieve maximum revenues in the company. The final delivery of a complete network was not observed but the delivery of the circuits that make it up, and this was a limiting factor for the study herein, which, however, brings an innovative proposition for the planning of private telecommunications network provisioning.

Frank Gilbreth and health care delivery method study driven learning.

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Towill, Denis R

2009-01-01

The purpose of this article is to look at method study, as devised by the Gilbreths at the beginning of the twentieth century, which found early application in hospital quality assurance and surgical "best practice". It has since become a core activity in all modern methods, as applied to healthcare delivery improvement programmes. The article traces the origin of what is now currently and variously called "business process re-engineering", "business process improvement" and "lean healthcare" etc., by different management gurus back to the century-old pioneering work of Frank Gilbreth. The outcome is a consistent framework involving "width", "length" and "depth" dimensions within which healthcare delivery systems can be analysed, designed and successfully implemented to achieve better and more consistent performance. Healthcare method (saving time plus saving motion) study is best practised as co-joint action learning activity "owned" by all "players" involved in the re-engineering process. However, although process mapping is a key step forward, in itself it is no guarantee of effective re-engineering. It is not even the beginning of the end of the change challenge, although it should be the end of the beginning. What is needed is innovative exploitation of method study within a healthcare organisational learning culture accelerated via the Gilbreth Knowledge Flywheel. It is shown that effective healthcare delivery pipeline improvement is anchored into a team approach involving all "players" in the system especially physicians. A comprehensive process study, constructive dialogue, proper and highly professional re-engineering plus managed implementation are essential components. Experience suggests "learning" is thereby achieved via "natural groups" actively involved in healthcare processes. The article provides a proven method for exploiting Gilbreths' outputs and their many successors in enabling more productive evidence-based healthcare delivery as summarised

Efficient and effective implementation of alternative project delivery methods.

Science.gov (United States)

2017-05-01

Over the past decade, the Maryland Department of Transportation State Highway : Administration (MDOT SHA) has implemented Alternative Project Delivery (APD) methods : in a number of transportation projects. While these innovative practices have produ...

A random network based, node attraction facilitated network evolution method

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WenJun Zhang

2016-03-01

Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

Do-it-yourself networks: a novel method of generating weighted networks.

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Shanafelt, D W; Salau, K R; Baggio, J A

2017-11-01

Network theory is finding applications in the life and social sciences for ecology, epidemiology, finance and social-ecological systems. While there are methods to generate specific types of networks, the broad literature is focused on generating unweighted networks. In this paper, we present a framework for generating weighted networks that satisfy user-defined criteria. Each criterion hierarchically defines a feature of the network and, in doing so, complements existing algorithms in the literature. We use a general example of ecological species dispersal to illustrate the method and provide open-source code for academic purposes.

Constructing an Intelligent Patent Network Analysis Method

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Chao-Chan Wu

2012-11-01

Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

Quasi-Experimental Study of the Effectiveness of an Integrated Service Delivery Network for the Frail Elderly

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Tourigny, Andre; Durand, Pierre J.; Bonin, Lucie; Hebert, Rejean; Rochette, Louis

2004-01-01

The aim of this study was to examine the effectiveness of a new, integrated service delivery (ISD) network of health and social services for frail elderly living in a semi-urban community. A quasi-experimental study was conducted from 1997 to 2000, with measures taken before implementation (T0) and every 12 months after implementation for a 3-year…

REAL TIME ANALYSIS OF WIRELESS CONTROLLER AREA NETWORK

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Gerardine Immaculate Mary

2014-09-01

Full Text Available It is widely known that Control Area Networks (CAN are used in real-time, distributed and parallel processing which cover manufacture plants, humanoid robots, networking fields, etc., In applications where wireless conditions are encountered it is convenient to continue the exchange of CAN frames within the Wireless CAN (WCAN. The WCAN considered in this research is based on wireless token ring protocol (WTRP; a MAC protocol for wireless networks to reduce the number of retransmissions due to collision and the wired counterpart CAN attribute on message based communication. WCAN uses token frame method to provide channel access to the nodes in the system. This method allow all the nodes to share common broadcast channel by taken turns in transmitting upon receiving the token frame which is circulating within the network for specified amount of time. This method provides high throughput in bounded latency environment, consistent and predictable delays and good packet delivery ratio. The most important factor to consider when evaluating a control network is the end-to-end time delay between sensors, controllers, and actuators. The correct operation of a control system depends on the timeliness of the data coming over the network, and thus, a control network should be able to guarantee message delivery within a bounded transmission time. The proposed WCAN is modeled and simulated using QualNet, and its average end to end delay and packet delivery ratio (PDR are calculated. The parameters boundaries of WCAN are evaluated to guarantee a maximum throughput and a minimum latency time, in the case of wireless communications, precisely WCAN.

Cut Based Method for Comparing Complex Networks.

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Liu, Qun; Dong, Zhishan; Wang, En

2018-03-23

Revealing the underlying similarity of various complex networks has become both a popular and interdisciplinary topic, with a plethora of relevant application domains. The essence of the similarity here is that network features of the same network type are highly similar, while the features of different kinds of networks present low similarity. In this paper, we introduce and explore a new method for comparing various complex networks based on the cut distance. We show correspondence between the cut distance and the similarity of two networks. This correspondence allows us to consider a broad range of complex networks and explicitly compare various networks with high accuracy. Various machine learning technologies such as genetic algorithms, nearest neighbor classification, and model selection are employed during the comparison process. Our cut method is shown to be suited for comparisons of undirected networks and directed networks, as well as weighted networks. In the model selection process, the results demonstrate that our approach outperforms other state-of-the-art methods with respect to accuracy.

A Systematic, Automated Network Planning Method

DEFF Research Database (Denmark)

Holm, Jens Åge; Pedersen, Jens Myrup

2006-01-01

This paper describes a case study conducted to evaluate the viability of a systematic, automated network planning method. The motivation for developing the network planning method was that many data networks are planned in an adhoc manner with no assurance of quality of the solution with respect...... structures, that are ready to implement in a real world scenario, are discussed in the end of the paper. These are in the area of ensuring line independence and complexity of the design rules for the planning method....

Social video content delivery

CERN Document Server

Wang, Zhi; Zhu, Wenwu

2016-01-01

This brief presents new architecture and strategies for distribution of social video content. A primary framework for socially-aware video delivery and a thorough overview of the possible approaches is provided. The book identifies the unique characteristics of socially-aware video access and social content propagation, revealing the design and integration of individual modules that are aimed at enhancing user experience in the social network context. The change in video content generation, propagation, and consumption for online social networks, has significantly challenged the traditional video delivery paradigm. Given the massive amount of user-generated content shared in online social networks, users are now engaged as active participants in the social ecosystem rather than as passive receivers of media content. This revolution is being driven further by the deep penetration of 3G/4G wireless networks and smart mobile devices that are seamlessly integrated with online social networking and media-sharing s...

Optimization of European call options considering physical delivery network and reservoir operation rules

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Cheng, Wei-Chen; Hsu, Nien-Sheng; Cheng, Wen-Ming; Yeh, William W.-G.

2011-10-01

This paper develops alternative strategies for European call options for water purchase under hydrological uncertainties that can be used by water resources managers for decision making. Each alternative strategy maximizes its own objective over a selected sequence of future hydrology that is characterized by exceedance probability. Water trade provides flexibility and enhances water distribution system reliability. However, water trade between two parties in a regional water distribution system involves many issues, such as delivery network, reservoir operation rules, storage space, demand, water availability, uncertainty, and any existing contracts. An option is a security giving the right to buy or sell an asset; in our case, the asset is water. We extend a flow path-based water distribution model to include reservoir operation rules. The model simultaneously considers both the physical distribution network as well as the relationships between water sellers and buyers. We first test the model extension. Then we apply the proposed optimization model for European call options to the Tainan water distribution system in southern Taiwan. The formulation lends itself to a mixed integer linear programming model. We use the weighing method to formulate a composite function for a multiobjective problem. The proposed methodology provides water resources managers with an overall picture of water trade strategies and the consequence of each strategy. The results from the case study indicate that the strategy associated with a streamflow exceedence probability of 50% or smaller should be adopted as the reference strategy for the Tainan water distribution system.

Link Prediction Methods and Their Accuracy for Different Social Networks and Network Metrics

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Fei Gao

2015-01-01

Full Text Available Currently, we are experiencing a rapid growth of the number of social-based online systems. The availability of the vast amounts of data gathered in those systems brings new challenges that we face when trying to analyse it. One of the intensively researched topics is the prediction of social connections between users. Although a lot of effort has been made to develop new prediction approaches, the existing methods are not comprehensively analysed. In this paper we investigate the correlation between network metrics and accuracy of different prediction methods. We selected six time-stamped real-world social networks and ten most widely used link prediction methods. The results of the experiments show that the performance of some methods has a strong correlation with certain network metrics. We managed to distinguish “prediction friendly” networks, for which most of the prediction methods give good performance, as well as “prediction unfriendly” networks, for which most of the methods result in high prediction error. Correlation analysis between network metrics and prediction accuracy of prediction methods may form the basis of a metalearning system where based on network characteristics it will be able to recommend the right prediction method for a given network.

Network modelling methods for FMRI.

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Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

2011-01-15

There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

Measurement of integrated healthcare delivery: a systematic review of methods and future research directions

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Martin Strandberg-Larsen

2009-02-01

Full Text Available Background: Integrated healthcare delivery is a policy goal of healthcare systems. There is no consensus on how to measure the concept, which makes it difficult to monitor progress. Purpose: To identify the different types of methods used to measure integrated healthcare delivery with emphasis on structural, cultural and process aspects. Methods: Medline/Pubmed, EMBASE, Web of Science, Cochrane Library, WHOLIS, and conventional internet search engines were systematically searched for methods to measure integrated healthcare delivery (published – April 2008. Results: Twenty-four published scientific papers and documents met the inclusion criteria. In the 24 references we identified 24 different measurement methods; however, 5 methods shared theoretical framework. The methods can be categorized according to type of data source: a questionnaire survey data, b automated register data, or c mixed data sources. The variety of concepts measured reflects the significant conceptual diversity within the field, and most methods lack information regarding validity and reliability. Conclusion: Several methods have been developed to measure integrated healthcare delivery; 24 methods are available and some are highly developed. The objective governs the method best used. Criteria for sound measures are suggested and further developments should be based on an explicit conceptual framework and focus on simplifying and validating existing methods.

Women's social networks and use of facility delivery services for uncomplicated births in North West Ethiopia: a community-based case-control study.

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Asrese, Kerebih; Adamek, Margaret E

2017-12-28

High maternal mortality has remained an unmet public health challenge in the developing world. Maternal mortality in Ethiopia is among the highest in the world. Since most maternal deaths occur during labor, delivery, and the immediate postpartum period, facility delivery with skilled birth attendants is recommended to reduce maternal mortality. Nonetheless, the majority of women in Ethiopia give birth at home. Individual attributes and availability and accessibility of services deter service utilization. The role of social networks that may facilitate or constrain service use is not well studied. Community-based case-control study was conducted between February and March 2014 in Jabi Tehinan District, North West Ethiopia. Retrospective data were collected from 134 women who had uncomplicated births at health facilities and 140 women who had uncomplicated births at home within a year preceding the survey. Interviews were held with eight women who had uncomplicated births at health facilities and 11 who had uncomplicated births at home. The quantitative data were entered and analyzed using SPSS for Windows versions 16.0 and hierarchical logistic regression model was used for analysis. The qualitative data were transcribed verbatim and data were used to substantiate the quantitative data. The results indicated that social network variables were significantly associated with the use of health facilities for delivery. Taking social networks into account improved the explanation of facility use for delivery services over women's individual attributes. Women embedded within homogeneous network members (Adjusted OR 2.53; 95% CI: 1.26-5.06) and embedded within high SBA endorsement networks (Adjusted OR 7.97; 95% CI: 4.07-12.16) were more likely to deliver at health facilities than their counterparts. Women living in urban areas (Adjusted OR 3.32; 95% CI: 1.37-8.05) and had better knowledge of obstetric complications (Adjusted OR 3.01; 95% CI: 1.46-6.18) were more likely to

Decreased rates of nosocomial endometritis and urinary tract infection after vaginal delivery in a French surveillance network, 1997-2003.

Science.gov (United States)

Ayzac, Louis; Caillat-Vallet, Emmanuelle; Girard, Raphaële; Chapuis, Catherine; Depaix, Florence; Dumas, Anne-Marie; Gignoux, Chantal; Haond, Catherine; Lafarge-Leboucher, Joëlle; Launay, Carine; Tissot-Guerraz, Françoise; Vincent, Agnès; Fabry, Jacques

2008-06-01

To identify independent risk factors for endometritis and urinary tract infection (UTI) after vaginal delivery, and to monitor changes in nosocomial infection rates and derive benchmarks for prevention. Prospective study. We analyzed routine surveillance data for all vaginal deliveries between January 1997 and December 2003 at 66 maternity units participating in the Mater Sud-Est surveillance network. Adjusted odds ratios for risk of endometritis or UTI were obtained using a logistic regression model. The overall incidence rates were 0.5% for endometritis and 0.3% for UTI. There was a significant decrease in the incidence and risk of endometritis but not of UTI during the 7-year period. Significant risk factors for endometritis were fever during labor, parity of 1, and instrumental delivery and/or manual removal of the placenta. Significant risk factors for UTI were urinary infection on admission, premature rupture of membranes (more than 12 hours before admission), blood loss of more than 800 mL, parity of 1, instrumental delivery, and receipt of more than 5 vaginal digital examinations. Each maternity unit received a poster showing graphs of the number of expected and observed cases of UTI and endometritis associated with vaginal deliveries, which enabled each maternity unit to determine their rank within the network and to initiate prevention programs. Although routine surveillance means additional work for maternity units, our results demonstrate the usefulness of regular targeted monitoring of risk factors and of the most common nosocomial infections in obstetrics. Most of the information needed for monitoring is already present in the patients' records.

Study of high-pressure cryogenic pumps with different methods of delivery control

International Nuclear Information System (INIS)

Braun, V.M.; Brailovskii, Y.L.; Pavlenko, Y.A.; Tsokalo, I.V.

1986-01-01

This paper describes new reciprocating pumps with smooth control of delivery in a running pump. Control is effected either by changing the length of the piston stroke or by changing the speed of the driving motor. The individual features of the two methods are described. In the first method (mechanical), delivery is controlled in the range 50 to 100%. A separate actuating mechanism is needed to connect the pump to an automatic control system. This method complicates the driving mechanism and increases the bulk and cost of production. In the second method of controlling the speed of the electric motor, an electric drive fitted with a frequency thyristor is used. AC induction motors series 4A working at current frequencies of 60 HZ are used. By this method, delivery control could be enhanced by 1.3 times. Comparative tests were made on pumps using the above methods of control. The tests demonstrated the possibilities of using the frequency thyristor converters. The complexity and high cost of EKT type drives is largely compensated by the convenience and simplicity of control in a wide range. The mechanical control is advantageous only in low-output units

Survey on Monitoring and Quality Controlling of the Mobile Biosignal Delivery.

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Pawar, Pravin A; Edla, Damodar R; Edoh, Thierry; Shinde, Vijay; van Beijnum, Bert-Jan

2017-10-31

A Mobile Patient Monitoring System (MPMS) acquires patient's biosignals and transmits them using wireless network connection to the decision-making module or healthcare professional for the assessment of patient's condition. A variety of wireless network technologies such as wireless personal area networks (e.g., Bluetooth), mobile ad-hoc networks (MANET), and infrastructure-based networks (e.g., WLAN and cellular networks) are in practice for biosignals delivery. The wireless network quality-of-service (QoS) requirements of biosignals delivery are mainly specified in terms of required bandwidth, acceptable delay, and tolerable error rate. An important research challenge in the MPMS is how to satisfy QoS requirements of biosignals delivery in the environment characterized by patient mobility, deployment of multiple wireless network technologies, and variable QoS characteristics of the wireless networks. QoS requirements are mainly application specific, while available QoS is largely dependent on QoS provided by wireless network in use. QoS provisioning refers to providing support for improving QoS experience of networked applications. In resource poor conditions, application adaptation may also be required to make maximum use of available wireless network QoS. This survey paper presents a survey of recent developments in the area of QoS provisioning for MPMS. In particular, our contributions are as follows: (1) overview of wireless networks and network QoS requirements of biosignals delivery; (2) survey of wireless networks' QoS performance evaluation for the transmission of biosignals; and (3) survey of QoS provisioning mechanisms for biosignals delivery in MPMS. We also propose integrating end-to-end QoS monitoring and QoS provisioning strategies in a mobile patient monitoring system infrastructure to support optimal delivery of biosignals to the healthcare professionals.

Provisional-Ideal-Point-Based Multi-objective Optimization Method for Drone Delivery Problem

Science.gov (United States)

Omagari, Hiroki; Higashino, Shin-Ichiro

2018-04-01

In this paper, we proposed a new evolutionary multi-objective optimization method for solving drone delivery problems (DDP). It can be formulated as a constrained multi-objective optimization problem. In our previous research, we proposed the "aspiration-point-based method" to solve multi-objective optimization problems. However, this method needs to calculate the optimal values of each objective function value in advance. Moreover, it does not consider the constraint conditions except for the objective functions. Therefore, it cannot apply to DDP which has many constraint conditions. To solve these issues, we proposed "provisional-ideal-point-based method." The proposed method defines a "penalty value" to search for feasible solutions. It also defines a new reference solution named "provisional-ideal point" to search for the preferred solution for a decision maker. In this way, we can eliminate the preliminary calculations and its limited application scope. The results of the benchmark test problems show that the proposed method can generate the preferred solution efficiently. The usefulness of the proposed method is also demonstrated by applying it to DDP. As a result, the delivery path when combining one drone and one truck drastically reduces the traveling distance and the delivery time compared with the case of using only one truck.

Impact of delivery mode on the colostrum microbiota composition.

Science.gov (United States)

Toscano, Marco; De Grandi, Roberta; Peroni, Diego Giampietro; Grossi, Enzo; Facchin, Valentina; Comberiati, Pasquale; Drago, Lorenzo

2017-09-25

Breast milk is a rich nutrient with a temporally dynamic nature. In particular, numerous alterations in the nutritional, immunological and microbiological content occur during the transition from colostrum to mature milk. The objective of our study was to evaluate the potential impact of delivery mode on the microbiota of colostrum, at both the quantitative and qualitative levels (bacterial abundance and microbiota network). Twenty-nine Italian mothers (15 vaginal deliveries vs 14 Cesarean sections) were enrolled in the study. The microbiota of colostrum samples was analyzed by next generation sequencing (Ion Torrent Personal Genome Machine). The colostrum microbiota network associated with Cesarean section and vaginal delivery was evaluated by means of the Auto Contractive Map (AutoCM), a mathematical methodology based on Artificial Neural Network (ANN) architecture. Numerous differences between Cesarean section and vaginal delivery colostrum were observed. Vaginal delivery colostrum had a significant lower abundance of Pseudomonas spp., Staphylococcus spp. and Prevotella spp. when compared to Cesarean section colostrum samples. Furthermore, the mode of delivery had a strong influence on the microbiota network, as Cesarean section colostrum showed a higher number of bacterial hubs if compared to vaginal delivery, sharing only 5 hubs. Interestingly, the colostrum of mothers who had a Cesarean section was richer in environmental bacteria than mothers who underwent vaginal delivery. Finally, both Cesarean section and vaginal delivery colostrum contained a greater number of anaerobic bacteria genera. The mode of delivery had a large impact on the microbiota composition of colostrum. Further studies are needed to better define the meaning of the differences we observed between Cesarean section and vaginal delivery colostrum microbiota.

An Improved Method for Magnetic Nanocarrier Drug Delivery across the Cell Membrane

Directory of Open Access Journals (Sweden)

Behzad Mehrafrooz

2018-01-01

Full Text Available One of the crucial issues in the pharmacological field is developing new drug delivery systems. The main concern is to develop new methods for improving the drug delivery efficiencies such as low disruptions, precise control of the target of delivery and drug sustainability. Nowadays, there are many various methods for drug delivery systems. Carbon-based nanocarriers are a new efficient tool for translocating drug into the defined area or cells inside the body. These nanocarriers can be functionalized with proteins, peptides and used to transport their freight to cells or defined areas. Since functionalized carbon-based nanocarriers show low toxicity and high biocompatibility, they are used in many nanobiotechnology fields. In this study, different shapes of nanocarrier are investigated, and the suitable magnetic field, which is applied using MRI for the delivery of the nanocarrier, is proposed. In this research, based on the force required to cross the membrane and MD simulations, the optimal magnetic field profile is designed. This optimal magnetic force field is derived from the mathematical model of the system and magnetic particle dynamics inside the nanocarrier. The results of this paper illustrate the effects of the nanocarrier’s shapes on the percentage of success in crossing the membrane and the optimal required magnetic field.

Multiple network interface core apparatus and method

Science.gov (United States)

Underwood, Keith D [Albuquerque, NM; Hemmert, Karl Scott [Albuquerque, NM

2011-04-26

A network interface controller and network interface control method comprising providing a single integrated circuit as a network interface controller and employing a plurality of network interface cores on the single integrated circuit.

Delivery Device and Method for Forming the Same

Science.gov (United States)

Ma, Peter X. (Inventor); Liu, Xiaohua (Inventor); McCauley, Laurie (Inventor)

2014-01-01

A delivery device includes a hollow container, and a plurality of biodegradable and/or erodible polymeric layers established in the container. A layer including a predetermined substance is established between each of the plurality of polymeric layers, whereby degradation of the polymeric layer and release of the predetermined substance occur intermittently. Methods for forming the device are also disclosed herein.

Structural reliability calculation method based on the dual neural network and direct integration method.

Science.gov (United States)

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Artificial neural network intelligent method for prediction

Science.gov (United States)

Trifonov, Roumen; Yoshinov, Radoslav; Pavlova, Galya; Tsochev, Georgi

2017-09-01

Accounting and financial classification and prediction problems are high challenge and researchers use different methods to solve them. Methods and instruments for short time prediction of financial operations using artificial neural network are considered. The methods, used for prediction of financial data as well as the developed forecasting system with neural network are described in the paper. The architecture of a neural network used four different technical indicators, which are based on the raw data and the current day of the week is presented. The network developed is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data.

A feasible method for clinical delivery verification and dose reconstruction in tomotherapy

International Nuclear Information System (INIS)

Kapatoes, J.M.; Olivera, G.H.; Ruchala, K.J.; Smilowitz, J.B.; Reckwerdt, P.J.; Mackie, T.R.

2001-01-01

Delivery verification is the process in which the energy fluence delivered during a treatment is verified. This verified energy fluence can be used in conjunction with an image in the treatment position to reconstruct the full three-dimensional dose deposited. A method for delivery verification that utilizes a measured database of detector signal is described in this work. This database is a function of two parameters, radiological path-length and detector-to-phantom distance, both of which are computed from a CT image taken at the time of delivery. Such a database was generated and used to perform delivery verification and dose reconstruction. Two experiments were conducted: a simulated prostate delivery on an inhomogeneous abdominal phantom, and a nasopharyngeal delivery on a dog cadaver. For both cases, it was found that the verified fluence and dose results using the database approach agreed very well with those using previously developed and proven techniques. Delivery verification with a measured database and CT image at the time of treatment is an accurate procedure for tomotherapy. The database eliminates the need for any patient-specific, pre- or post-treatment measurements. Moreover, such an approach creates an opportunity for accurate, real-time delivery verification and dose reconstruction given fast image reconstruction and dose computation tools

A new fault detection method for computer networks

International Nuclear Information System (INIS)

Lu, Lu; Xu, Zhengguo; Wang, Wenhai; Sun, Youxian

2013-01-01

Over the past few years, fault detection for computer networks has attracted extensive attentions for its importance in network management. Most existing fault detection methods are based on active probing techniques which can detect the occurrence of faults fast and precisely. But these methods suffer from the limitation of traffic overhead, especially in large scale networks. To relieve traffic overhead induced by active probing based methods, a new fault detection method, whose key is to divide the detection process into multiple stages, is proposed in this paper. During each stage, only a small region of the network is detected by using a small set of probes. Meanwhile, it also ensures that the entire network can be covered after multiple detection stages. This method can guarantee that the traffic used by probes during each detection stage is small sufficiently so that the network can operate without severe disturbance from probes. Several simulation results verify the effectiveness of the proposed method

A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks

Directory of Open Access Journals (Sweden)

Ke-yan Liu

2017-05-01

Full Text Available This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO. Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA. In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible.

Binary Classification Method of Social Network Users

Directory of Open Access Journals (Sweden)

I. A. Poryadin

2017-01-01

Full Text Available The subject of research is a binary classification method of social network users based on the data analysis they have placed. Relevance of the task to gain information about a person by examining the content of his/her pages in social networks is exemplified. The most common approach to its solution is a visual browsing. The order of the regional authority in our country illustrates that its using in school education is needed. The article shows restrictions on the visual browsing of pupil’s pages in social networks as a tool for the teacher and the school psychologist and justifies that a process of social network users’ data analysis should be automated. Explores publications, which describe such data acquisition, processing, and analysis methods and considers their advantages and disadvantages. The article also gives arguments to support a proposal to study the classification method of social network users. One such method is credit scoring, which is used in banks and credit institutions to assess the solvency of clients. Based on the high efficiency of the method there is a proposal for significant expansion of its using in other areas of society. The possibility to use logistic regression as the mathematical apparatus of the proposed method of binary classification has been justified. Such an approach enables taking into account the different types of data extracted from social networks. Among them: the personal user data, information about hobbies, friends, graphic and text information, behaviour characteristics. The article describes a number of existing methods of data transformation that can be applied to solve the problem. An experiment of binary gender-based classification of social network users is described. A logistic model obtained for this example includes multiple logical variables obtained by transforming the user surnames. This experiment confirms the feasibility of the proposed method. Further work is to define a system

Preclinical evaluation of gene delivery methods for the treatment of loco-regional disease in breast cancer.

LENUS (Irish Health Repository)

Rajendran, Simon

2011-04-01

Preclinical results with various gene therapy strategies indicate significant potential for new cancer treatments. However, many therapeutics fail at clinical trial, often due to differences in tissue physiology between animal models and humans, and tumor phenotype variation. Clinical data relevant to treatment strategies may be generated prior to clinical trial through experimentation using intact patient tissue ex vivo. We developed a novel tumor slice model culture system that is universally applicable to gene delivery methods, using a realtime luminescence detection method to assess gene delivery. Methods investigated include viruses (adenovirus [Ad] and adeno-associated virus), lipofection, ultrasound (US), electroporation and naked DNA. Viability and tumor populations within the slices were well maintained for seven days, and gene delivery was qualitatively and quantitatively examinable for all vectors. Ad was the most efficient gene delivery vector with transduction efficiency >50%. US proved the optimal non-viral gene delivery method in human tumor slices. The nature of the ex vivo culture system permitted examination of specific elements. Parameters shown to diminish Ad gene delivery included blood, regions of low viability and secondary disease. US gene delivery was significantly reduced by blood and skin, while tissue hyperthermia improved gene delivery. US achieved improved efficacy for secondary disease. The ex vivo model was also suitable for examination of tissue-specific effects on vector expression, with Ad expression mediated by the CXCR4 promoter shown to provide a tumor selective advantage over the ubiquitously active cytomegalovirus promoter. In conclusion, this is the first study incorporating patient tissue models in comparing gene delivery from various vectors, providing knowledge on cell-type specificity and examining the crucial biological factors determining successful gene delivery. The results highlight the importance of in

Preclinical evaluation of gene delivery methods for the treatment of loco-regional disease in breast cancer.

LENUS (Irish Health Repository)

Rajendran, Simon

2012-01-31

Preclinical results with various gene therapy strategies indicate significant potential for new cancer treatments. However, many therapeutics fail at clinical trial, often due to differences in tissue physiology between animal models and humans, and tumor phenotype variation. Clinical data relevant to treatment strategies may be generated prior to clinical trial through experimentation using intact patient tissue ex vivo. We developed a novel tumor slice model culture system that is universally applicable to gene delivery methods, using a realtime luminescence detection method to assess gene delivery. Methods investigated include viruses (adenovirus [Ad] and adeno-associated virus), lipofection, ultrasound (US), electroporation and naked DNA. Viability and tumor populations within the slices were well maintained for seven days, and gene delivery was qualitatively and quantitatively examinable for all vectors. Ad was the most efficient gene delivery vector with transduction efficiency >50%. US proved the optimal non-viral gene delivery method in human tumor slices. The nature of the ex vivo culture system permitted examination of specific elements. Parameters shown to diminish Ad gene delivery included blood, regions of low viability and secondary disease. US gene delivery was significantly reduced by blood and skin, while tissue hyperthermia improved gene delivery. US achieved improved efficacy for secondary disease. The ex vivo model was also suitable for examination of tissue-specific effects on vector expression, with Ad expression mediated by the CXCR4 promoter shown to provide a tumor selective advantage over the ubiquitously active cytomegalovirus promoter. In conclusion, this is the first study incorporating patient tissue models in comparing gene delivery from various vectors, providing knowledge on cell-type specificity and examining the crucial biological factors determining successful gene delivery. The results highlight the importance of in

Application of nanohydrogels in drug delivery systems: recent patents review.

Science.gov (United States)

Dalwadi, Chintan; Patel, Gayatri

2015-01-01

Nanohydrogel combines the advantages of hydrogel and nano particulate systems. Similar to the hydrogel and macrogel, nanohydrogel can protect the drug and control drug release by stimuli responsive conformation or biodegradable bond into the polymer networks. Nanohydrogel has drawn huge interest due to their potential applications, such as carrier in target-specific controlled drug delivery, absorbents, chemical/biological sensors, and bio-mimetic materials. Similar to the nanoparticles, stimuli responsive nanohydrogel can easily be delivered in the liquid form for parenteral drug delivery application. This review highlights the methods to prepare nanohydrogel based on natural and synthetic polymers for diverse applications in drug delivery. It also encompasses the drug loading and drug release mechanism of the nanohydrogel formulation and patents related to the composition and chemical methods for preparation of nanohydrogel formulation with current status in clinical trials.

Reduction Method for Active Distribution Networks

DEFF Research Database (Denmark)

Raboni, Pietro; Chen, Zhe

2013-01-01

On-line security assessment is traditionally performed by Transmission System Operators at the transmission level, ignoring the effective response of distributed generators and small loads. On the other hand the required computation time and amount of real time data for including Distribution...... Networks also would be too large. In this paper an adaptive aggregation method for subsystems with power electronic interfaced generators and voltage dependant loads is proposed. With this tool may be relatively easier including distribution networks into security assessment. The method is validated...... by comparing the results obtained in PSCAD® with the detailed network model and with the reduced one. Moreover the control schemes of a wind turbine and a photovoltaic plant included in the detailed network model are described....

A divisive spectral method for network community detection

International Nuclear Information System (INIS)

Cheng, Jianjun; Li, Longjie; Yao, Yukai; Chen, Xiaoyun; Leng, Mingwei; Lu, Weiguo

2016-01-01

Community detection is a fundamental problem in the domain of complex network analysis. It has received great attention, and many community detection methods have been proposed in the last decade. In this paper, we propose a divisive spectral method for identifying community structures from networks which utilizes a sparsification operation to pre-process the networks first, and then uses a repeated bisection spectral algorithm to partition the networks into communities. The sparsification operation makes the community boundaries clearer and sharper, so that the repeated spectral bisection algorithm extract high-quality community structures accurately from the sparsified networks. Experiments show that the combination of network sparsification and a spectral bisection algorithm is highly successful, the proposed method is more effective in detecting community structures from networks than the others. (paper: interdisciplinary statistical mechanics)

Dominant mechanisms for the delivery of fine sediment and phosphorus to fluvial networks draining grassland dominated headwater catchments.

Science.gov (United States)

Perks, M T; Owen, G J; Benskin, C McW H; Jonczyk, J; Deasy, C; Burke, S; Reaney, S M; Haygarth, P M

2015-08-01

Recent advances in monitoring technology have enabled high frequency, in-situ measurements of total phosphorus and total reactive phosphorus to be undertaken with high precision, whilst turbidity can provide an excellent surrogate for suspended sediment. Despite these measurements being fundamental to understanding the mechanisms and flow paths that deliver these constituents to river networks, there is a paucity of such data for headwater agricultural catchments. The aim of this paper is to deduce the dominant mechanisms for the delivery of fine sediment and phosphorus to an upland river network in the UK through characterisation of the temporal variability of hydrological fluxes, and associated soluble and particulate concentrations for the period spanning March 2012-February 2013. An assessment of the factors producing constituent hysteresis is undertaken following factor analysis (FA) on a suite of measured environmental variables representing the fluvial and wider catchment conditions prior to, and during catchment-wide hydrological events. Analysis indicates that suspended sediment is delivered to the fluvial system predominantly via rapidly responding pathways driven by event hydrology. However, evidence of complex, figure-of-eight hysteresis is observed following periods of hydrological quiescence, highlighting the importance of preparatory processes. Sediment delivery via a slow moving, probably sub-surface pathway does occur, albeit infrequently and during low magnitude events at the catchment outlet. Phosphorus is revealed to have a distinct hysteretic response to that of suspended sediment, with sub-surface pathways dominating. However, high magnitude events were observed to exhibit threshold-like behaviour, whereby activation and connection of usually disconnected depositional zones to the fluvial networks results in the movement of vast phosphorus fluxes. Multiple pathways are observed for particulate and soluble constituents, highlighting the

Method and system for mesh network embedded devices

Science.gov (United States)

Wang, Ray (Inventor)

2009-01-01

A method and system for managing mesh network devices. A mesh network device with integrated features creates an N-way mesh network with a full mesh network topology or a partial mesh network topology.

Effective teaching strategies and methods of delivery for patient education: a systematic review and practice guideline recommendations.

Science.gov (United States)

Friedman, Audrey Jusko; Cosby, Roxanne; Boyko, Susan; Hatton-Bauer, Jane; Turnbull, Gale

2011-03-01

The objective of this study was to determine effective teaching strategies and methods of delivery for patient education (PE). A systematic review was conducted and reviews with or without meta-analyses, which examined teaching strategies and methods of delivery for PE, were included. Teaching strategies identified are traditional lectures, discussions, simulated games, computer technology, written material, audiovisual sources, verbal recall, demonstration, and role playing. Methods of delivery focused on how to deliver the teaching strategies. Teaching strategies that increased knowledge, decreased anxiety, and increased satisfaction included computer technology, audio and videotapes, written materials, and demonstrations. Various teaching strategies used in combination were similarly successful. Moreover, structured-, culturally appropriate- and patient-specific teachings were found to be better than ad hoc teaching or generalized teaching. Findings provide guidance for establishing provincial standards for the delivery of PE. Recommendations concerning the efficacy of the teaching strategies and delivery methods are provided.

A Method for Routing Packets Across Multiple Paths in NoCs with In-Order Delivery and Fault-Tolerance Gaurantees

Directory of Open Access Journals (Sweden)

Srinivasan Murali

2007-01-01

Full Text Available Networks on Chips (NoCs are required to tackle the increasing delay and poor scalability issues of bus-based communication architectures. Many of today's NoC designs are based on single path routing. By utilizing multiple paths for routing, congestion in the network is reduced significantly, which translates to improved network performance or reduced network bandwidth requirements and power consumption. Multiple paths can also be utilized to achieve spatial redundancy, which helps in achieving tolerance against faults or errors in the NoC. A major problem with multipath routing is that packets can reach the destination in an out-of-order fashion, while many applications require in-order packet delivery. In this work, we present a multipath routing strategy that guarantees in-order packet delivery for NoCs. It is based on the idea of routing packets on partially nonintersecting paths and rebuilding packet order at path reconvergent nodes. We present a design methodology that uses the routing strategy to optimally spread the traffic in the NoC to minimize the network bandwidth needs and power consumption. We also integrate support for tolerance against transient and permanent failures in the NoC links in the methodology by utilizing spatial and temporal redundancy for transporting packets. Our experimental studies show large reduction in network bandwidth requirements (36.86% on average and power consumption (30.51% on average compared to single-path systems. The area overhead of the proposed scheme is small (a modest 5% increase in network area. Hence, it is practical to be used in the on-chip domain.

Oxygen delivery in irradiated normal tissue

Energy Technology Data Exchange (ETDEWEB)

Kiani, M.F.; Ansari, R. [Univ. of Tennessee Health Science Center, Memphis, TN (United States). School of Biomedical Engineering; Gaber, M.W. [St. Jude Children' s Research Hospital, Memphis, TN (United States)

2003-03-01

Ionizing radiation exposure significantly alters the structure and function of microvascular networks, which regulate delivery of oxygen to tissue. In this study we use a hamster cremaster muscle model to study changes in microvascular network parameters and use a mathematical model to study the effects of these observed structural and microhemodynamic changes in microvascular networks on oxygen delivery to the tissue. Our experimental observations indicate that in microvascular networks while some parameters are significantly affected by irradiation (e.g. red blood cell (RBC) transit time), others remain at the control level (e.g. RBC path length) up to 180 days post-irradiation. The results from our mathematical model indicate that tissue oxygenation patterns are significantly different in irradiated normal tissue as compared to age-matched controls and the differences are apparent as early as 3 days post irradiation. However, oxygen delivery to irradiated tissue was not found to be significantly different from age matched controls at any time between 7 days to 6 months post-irradiation. These findings indicate that microvascular late effects in irradiated normal tissue may be due to factors other than compromised tissue oxygenation. (author)

Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

Science.gov (United States)

Baker-Doyle, Kira J.

2015-01-01

Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

Multilevel method for modeling large-scale networks.

Energy Technology Data Exchange (ETDEWEB)

Safro, I. M. (Mathematics and Computer Science)

2012-02-24

Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

Status of DOE information network modifications

International Nuclear Information System (INIS)

Fuchs, R.

1988-01-01

This paper provides an update on changes that have been made or are taking place to the Department of Energy's (DOE) National Information Network. Areas of focus are as follows: data acquisition from commercial disposal site operators, specifically, the information delivery system called Manifest Information Management System; improved access methods to DOE Information Network; progress on personal computer interfaces, and availability of end user support

[Methods of pushing at vaginal delivery and pelvi-perineal consequences. Review].

Science.gov (United States)

Ratier, N; Balenbois, E; Letouzey, V; Marès, P; de Tayrac, R

2015-03-01

The main objective of that review was to evaluate the pelvi-perineal consequences of the different methods of pushing at vaginal delivery. A review on PubMed, the Cochrane Library and EM-Premium was performed from 1984 to 2014. Among 29 manuscripts analysed, only nine randomised controlled trials (including one meta-analysis of three trials) comparing Valsalva and spontaneous pushing were selected. A 10 th study, secondary analysis of a randomized controlled trial comparing different methods of perineal protection (warm compresses, massage and manual protection), was also selected. Two trials have shown that spontaneous pushing reduces the risk of perineal tears, but studies were heterogeneous and discordant results do not allowed definitive conclusions. Results on the duration of the second stage of labour are conflicting. The method of pushing does not seem to affect the rate of episiotomy, instrumental delivery and cesarean section. Maternal satisfaction seems to be better after spontaneous pushing. It seems that there is no negative effect of spontaneous pushing on neonate well-being, and one study has shown a significant improvement of prenatal fetal parameters during the expulsive phase. According to current knowledge, both techniques of pushing during the expulsive phase at delivery seem comparable in terms of duration, risk of perineal tears and neonatal outcome. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Comparison of different decontaminant delivery methods for sterilizing unoccupied commercial airliner cabins

Energy Technology Data Exchange (ETDEWEB)

Chen, Xi; Chen, Qingyan [National Air Transport Center of Excellence for Research in the Intermodal Transport Environment (RITE), School of Mechanical Engineering, Purdue University, 585 Purdue Mall, West Lafayette, IN 47905 (United States)

2010-09-15

Effective decontamination is crucial if an airliner cabin is contaminated by biological contaminants, such as infectious disease viruses or intentionally released biological agents. This study used computational fluid dynamics (CFD) method as a tool and vaporized hydrogen peroxide (VHP) as an exemplary decontaminant and Geobacillus stearothermophilus spores as a simulant contaminant to investigate three VHP delivery methods for sterilizing two different airliner cabins. The CFD first determined the airflow and the transient distributions of the contaminant and decontaminant in cabins. Auxiliary equations were implemented into the CFD model for evaluating efficacy of the sterilization process. The improved CFD model was validated by the measured airflow and simulated contaminant distributions obtained from a cabin mockup and the measured efficacy data from the literature. The three decontaminant delivery methods were (1) to supply the mixed VHP and air through the environmental control system of a cabin, (2) to send mixed VHP and air through a front door and to extract them from a back door of a cabin, and (3) to send directly VHP to a cabin and enhance the mixing with air in the cabin by fans. The two air cabins studied were a single-aisle and a twin-aisle airliner one. The results show that the second decontaminant delivery method (displacement method) was the best because the VHP distributions in the cabins were most uniform, the sterilization time was moderate, and the corrosion risk was low. The method displaced the existing air by the air/disinfectant solution, rather than dispersive mixing as the other two methods. (author)

Sampling of temporal networks: Methods and biases

Science.gov (United States)

Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter

2017-11-01

Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.

A flood-based information flow analysis and network minimization method for gene regulatory networks.

Science.gov (United States)

Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

2013-04-24

Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

Mental Illness Stigma Intervention in African Americans: Examining Two Delivery Methods.

Science.gov (United States)

Vinson, Ebony S; Abdullah, Tahirah; Brown, Tamara L

2016-05-01

Stigma surrounding mental illness and mental health treatment remains a significant problem, particularly among African Americans. This study sought to examine the effects of 2 intervention delivery methods in reducing reported stigma. African Americans (n = 158) were nonrandomly assigned to an in-person contact or video condition and administered a survey immediately before, after, and 2 weeks following the stigma intervention. The in vivo contact condition consisted of an African American man discussing his experiences with mental illness and psychotherapy. The session was recorded, and the recording was used for the video condition. There were no significant effects based on delivery method; however, there was a significant effect for time on stigma and help-seeking attitude measures. Further research is needed to determine the overall effectiveness of the intervention.

An improved sampling method of complex network

Science.gov (United States)

Gao, Qi; Ding, Xintong; Pan, Feng; Li, Weixing

2014-12-01

Sampling subnet is an important topic of complex network research. Sampling methods influence the structure and characteristics of subnet. Random multiple snowball with Cohen (RMSC) process sampling which combines the advantages of random sampling and snowball sampling is proposed in this paper. It has the ability to explore global information and discover the local structure at the same time. The experiments indicate that this novel sampling method could keep the similarity between sampling subnet and original network on degree distribution, connectivity rate and average shortest path. This method is applicable to the situation where the prior knowledge about degree distribution of original network is not sufficient.

A Method for Upper Bounding on Network Access Speed

DEFF Research Database (Denmark)

Knudsen, Thomas Phillip; Patel, A.; Pedersen, Jens Myrup

2004-01-01

This paper presents a method for calculating an upper bound on network access speed growth and gives guidelines for further research experiments and simulations. The method is aimed at providing a basis for simulation of long term network development and resource management.......This paper presents a method for calculating an upper bound on network access speed growth and gives guidelines for further research experiments and simulations. The method is aimed at providing a basis for simulation of long term network development and resource management....

On-chip power delivery and management

CERN Document Server

Vaisband, Inna P; Popovich, Mikhail; Mezhiba, Andrey V; Köse, Selçuk; Friedman, Eby G

2016-01-01

This book describes methods for distributing power in high speed, high complexity integrated circuits with power levels exceeding many tens of watts and power supplies below a volt. It provides a broad and cohesive treatment of power delivery and management systems and related design problems, including both circuit network models and design techniques for on-chip decoupling capacitors, providing insight and intuition into the behavior and design of on-chip power distribution systems. Organized into subareas to provide a more intuitive flow to the reader, this fourth edition adds more than a hundred pages of new content, including inductance models for interdigitated structures, design strategies for multi-layer power grids, advanced methods for efficient power grid design and analysis, and methodologies for simultaneously placing on-chip multiple power supplies and decoupling capacitors. The emphasis of this additional material is on managing the complexity of on-chip power distribution networks.

Biomimetic oral mucin from polymer micelle networks

Science.gov (United States)

Authimoolam, Sundar Prasanth

Mucin networks are formed by the complexation of bottlebrush-like mucin glycoprotein with other small molecule glycoproteins. These glycoproteins create nanoscale strands that then arrange into a nanoporous mesh. These networks play an important role in ensuring surface hydration, lubricity and barrier protection. In order to understand the functional behavior in mucin networks, it is important to decouple their chemical and physical effects responsible for generating the fundamental property-function relationship. To achieve this goal, we propose to develop a synthetic biomimetic mucin using a layer-by-layer (LBL) deposition approach. In this work, a hierarchical 3-dimensional structures resembling natural mucin networks was generated using affinity-based interactions on synthetic and biological surfaces. Unlike conventional polyelectrolyte-based LBL methods, pre-assembled biotin-functionalized filamentous (worm-like) micelles was utilized as the network building block, which from complementary additions of streptavidin generated synthetic networks of desired thickness. The biomimetic nature in those synthetic networks are studied by evaluating its structural and bio-functional properties. Structurally, synthetic networks formed a nanoporous mesh. The networks demonstrated excellent surface hydration property and were able capable of microbial capture. Those functional properties are akin to that of natural mucin networks. Further, the role of synthetic mucin as a drug delivery vehicle, capable of providing localized and tunable release was demonstrated. By incorporating antibacterial curcumin drug loading within synthetic networks, bacterial growth inhibition was also demonstrated. Thus, such bioactive interfaces can serve as a model for independently characterizing mucin network properties and through its role as a drug carrier vehicle it presents exciting future opportunities for localized drug delivery, in regenerative applications and as bio

SCM: A method to improve network service layout efficiency with network evolution

Science.gov (United States)

Zhao, Qi; Zhang, Chuanhao

2017-01-01

Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of “software defined network + network function virtualization” (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently. PMID:29267299

SCM: A method to improve network service layout efficiency with network evolution.

Science.gov (United States)

Zhao, Qi; Zhang, Chuanhao; Zhao, Zheng

2017-01-01

Network services are an important component of the Internet, which are used to expand network functions for third-party developers. Network function virtualization (NFV) can improve the speed and flexibility of network service deployment. However, with the evolution of the network, network service layout may become inefficient. Regarding this problem, this paper proposes a service chain migration (SCM) method with the framework of "software defined network + network function virtualization" (SDN+NFV), which migrates service chains to adapt to network evolution and improves the efficiency of the network service layout. SCM is modeled as an integer linear programming problem and resolved via particle swarm optimization. An SCM prototype system is designed based on an SDN controller. Experiments demonstrate that SCM could reduce the network traffic cost and energy consumption efficiently.

A novel community detection method in bipartite networks

Science.gov (United States)

Zhou, Cangqi; Feng, Liang; Zhao, Qianchuan

2018-02-01

Community structure is a common and important feature in many complex networks, including bipartite networks, which are used as a standard model for many empirical networks comprised of two types of nodes. In this paper, we propose a two-stage method for detecting community structure in bipartite networks. Firstly, we extend the widely-used Louvain algorithm to bipartite networks. The effectiveness and efficiency of the Louvain algorithm have been proved by many applications. However, there lacks a Louvain-like algorithm specially modified for bipartite networks. Based on bipartite modularity, a measure that extends unipartite modularity and that quantifies the strength of partitions in bipartite networks, we fill the gap by developing the Bi-Louvain algorithm that iteratively groups the nodes in each part by turns. This algorithm in bipartite networks often produces a balanced network structure with equal numbers of two types of nodes. Secondly, for the balanced network yielded by the first algorithm, we use an agglomerative clustering method to further cluster the network. We demonstrate that the calculation of the gain of modularity of each aggregation, and the operation of joining two communities can be compactly calculated by matrix operations for all pairs of communities simultaneously. At last, a complete hierarchical community structure is unfolded. We apply our method to two benchmark data sets and a large-scale data set from an e-commerce company, showing that it effectively identifies community structure in bipartite networks.

Fault Tolerant Real-Time Networks

National Research Council Canada - National Science Library

Zakhor, Avideh; Henzinger, Thomas; Trevedi, Kishor; Ammar, Mostafa; Lynch, Nancy; Shin, Kang

2007-01-01

.... We have focused on multimedia delivery in traditional client-server architectures, both in the case of the Internet and wireless networks, as well as on peer-to-peer content delivery and on mobile ad-hoc networks...

Responsive and resilient supply chain network design under operational and disruption risks with delivery lead-time sensitive customers

DEFF Research Database (Denmark)

Fattahi, Mohammad; Govindan, Kannan; Keyvanshokooh, Esmaeil

2017-01-01

We address a multi-period supply chain (SC) network design where demands of customers depend on facilities serving them based on their delivery lead-times. Potential customer demands are stochastic, and facilities’ capacity varies randomly because of possible disruptions. Accordingly, we develop...... a multi-stage stochastic program, and model disruptions’ effect on facilities’ capacity. The SC responsiveness risk is limited and, to obtain a resilient network, both mitigation and contingency strategies are exploited. Computational results on a real-life case study and randomly generated problem...... instances demonstrate the model's applicability, risk-measurement policies’ performance, and the influence of mitigation and contingency strategies on SC's resiliency....

A new method to construct co-author networks

Science.gov (United States)

Liu, Jie; Li, Yunpeng; Ruan, Zichan; Fu, Guangyuan; Chen, Xiaowu; Sadiq, Rehan; Deng, Yong

2015-02-01

In this paper, we propose a new method to evaluate the importance of nodes in a given network. The proposed method is based on the PageRank algorithm. However, we have made necessary improvements to combine the importance of the node itself and that of its community status. First, we propose an improved method to better evaluate the real impact of a paper. The proposed method calibrates the real influence of a paper over time. Then we propose a scheme of evaluating the contribution of each author in a paper. We later develop a new method to combine the information of the author itself and the structure of the co-author network. We use the number of co-authorship to calculate the effective distance between two authors, and evaluate the strength of their influence to each other with the law of gravity. The strength of influence is used to build a new network of authors, which is a comprehensive topological representation of both the quality of the node and its role in network. Finally, we apply our method to the Erdos co-author community and AMiner Citation Network to identify the most influential authors.

A new hierarchical method to find community structure in networks

Science.gov (United States)

Saoud, Bilal; Moussaoui, Abdelouahab

2018-04-01

Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

Integrated project delivery methods for energy renovation of social housing

Directory of Open Access Journals (Sweden)

Tadeo Baldiri Salcedo Rahola

2015-11-01

Full Text Available Optimised project delivery methods forsocial housing energy renovations European Social Housing Organisations (SHOs are currently facing challenging times. The ageing of their housing stock and the economic crisis, which has affected both their finances and the finances of their tenants, are testing their capacity to stick to their aim of providing decent and affordable housing. Housing renovation projects offer the possibility of upgrading the health and comfort levels of their old housing stock to current standards and improve energy efficiency, and this solution also addresses the fuel poverty problems suffered by some tenants. Unfortunately, the limited financial capacity of SHOs is hampering the scale of housing renovation projects and the energy savings achieved.  At the same time, the renovation of the existing housing stock is seen as one of the most promising alternative routes to achieving the ambitious CO2 emissions reduction targets set by European authorities – namely, to reduce EU CO2 emissions to 20% below their 1990 levels by 2020. The synergy between European targets and the aims of SHOs has been addressed by the energy policies of the member states, which focus on the potential energy savings achievable by renovating social housing. In fact, the European initiatives have prioritised energy savings in social housing renovations to such an extent that these are referred to as ‘energy renovations’. Energy renovation is therefore a renovation project with higher energy savings target than a regular renovation project. In total, European SHOs own 21.5 million dwellings representing around 9.4% of the total housing stock. Each SHO owns a large number of dwellings, which means there are fewer people to convince of the need to make energy savings through building renovations, maximising the potentially high impact of decisions. Moreover, SHOs are responsible for maintaining and upgrading their properties in order to continue

The association between cesarean delivery on maternal request and method of newborn feeding in China.

Directory of Open Access Journals (Sweden)

Xinxue Liu

Full Text Available Cesarean delivery has increased significantly during the last decades. This study aimed to investigate the association between planned mode of delivery and method of feeding.A cohort was created retrospectively using data from a population-based maternal and child health surveillance system, which covers 27 study sites in China from 1993 to 2006. The cohort consisted of 431,704 women for analysis, including 22,462 women with planned cesarean delivery on maternal request (CDMR and 409,242 women with planned vaginal delivery (VD. Logistic regression models were used to examine the association between mode of delivery and method of feeding adjusting for selected covariates. In this cohort, 398,176 (92.2% women exclusively breastfed their baby, 28,798 (6.7% women chose mixed feeding, and 4,730 (1.1% women chose formula feeding before hospital discharge. Women who planned CDMR were less likely to exclusively breastfeed and more likely to formula feed their babies than those who planned VD. After adjusting for covariates, the odds ratios were 0.85 (95% CI: 0.81-0.89 for exclusive breastfeeding and 1.61 (95% CI: 1.45-1.79 for formula feeding. Associations between planned mode of delivery and method of feeding in the south, north, rural and urban areas yielded similar results.This study demonstrated that planned CDMR was associated with a lower rate of exclusive breastfeeding and a higher rate of formula feeding in a low-risk Chinese population.

A low complexity method for the optimization of network path length in spatially embedded networks

International Nuclear Information System (INIS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li; Ming, Yong; Chen, Sheng-Yong; Wang, Wan-Liang

2014-01-01

The average path length of a network is an important index reflecting the network transmission efficiency. In this paper, we propose a new method of decreasing the average path length by adding edges. A new indicator is presented, incorporating traffic flow demand, to assess the decrease in the average path length when a new edge is added during the optimization process. With the help of the indicator, edges are selected and added into the network one by one. The new method has a relatively small time computational complexity in comparison with some traditional methods. In numerical simulations, the new method is applied to some synthetic spatially embedded networks. The result shows that the method can perform competitively in decreasing the average path length. Then, as an example of an application of this new method, it is applied to the road network of Hangzhou, China. (paper)

Comet Assay: A Method to Evaluate Genotoxicity of Nano-Drug Delivery System

Science.gov (United States)

Vandghanooni, Somayeh; Eskandani, Morteza

2011-01-01

Introduction Drug delivery systems could induce cellular toxicity as side effect of nanomaterials. The mechanism of toxicity usually involves DNA damage. The comet assay or single cell gel electrophoresis (SCGE) is a sensitive method for detecting strand damages in the DNA of a cell with applications in genotoxicity testing and molecular epidemiology as well as fundamental research in DNA damage and repair. Methods In the current study, we reviewed recent drug delivery researches related to SCGE. Results We found that one preference for choosing the assay is that comet images may result from apoptosis-mediated nuclear fragmentation. This method has been widely used over the last decade in several different areas. Overall cells, such as cultured cells are embedded in agarose on a microscope slide, lysed with detergent, and treated with high salt. Nucleoids are supercoiled DNA form. When the slide is faced to alkaline electrophoresis any breakages present in the DNA cause the supercoiling to relax locally and loops of DNA extend toward the anode as a ‘‘comet tail’’. Conclusion This article provides a relatively comprehensive review upon potentiality of the comet assay for assessment of DNA damage and accordingly it can be used as an informative platform in genotoxicity studies of drug delivery systems. PMID:23678412

Primary health care service delivery networks for the prevention and management of type 2 diabetes: using social network methods to describe interorganisational collaboration in a rural setting.

Science.gov (United States)

McDonald, Julie; Jayasuriya, Rohan; Harris, Mark Fort

2011-01-01

Adults with type 2 diabetes or with behavioural risk factors require comprehensive and well coordinated responses from a range of health care providers who often work in different organisational settings. This study examines three types of collaborative links between organisations involved in a rural setting. Social network methods were employed using survey data on three types of links, and data was collected from a purposive sample of 17 organisations representing the major provider types. The analysis included a mix of unconfirmed and confirmed links, and network measures. General practices were the most influential provider group in initiating referrals, and they referred to the broadest range of organisations in the network. Team care arrangements formed a small part of the general practice referral network. They were used more for access to private sector allied health care providers and less for sharing care with public sector health services. Involvement in joint programs/activities was limited to public and non-government sector services, with no participation from the private sector. The patterns of interactions suggest that informal referral networks provide access to services and coordination of care for individual patients with diabetes. Two population subgroups would benefit from more proactive approaches to ensure equitable access to services and coordination of care across organisational boundaries: people with more complex health care needs and people at risk of developing diabetes.

Spectral Analysis Methods of Social Networks

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P. G. Klyucharev

2017-01-01

Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work

Optical multicast system for data center networks.

Science.gov (United States)

Samadi, Payman; Gupta, Varun; Xu, Junjie; Wang, Howard; Zussman, Gil; Bergman, Keren

2015-08-24

We present the design and experimental evaluation of an Optical Multicast System for Data Center Networks, a hardware-software system architecture that uniquely integrates passive optical splitters in a hybrid network architecture for faster and simpler delivery of multicast traffic flows. An application-driven control plane manages the integrated optical and electronic switched traffic routing in the data plane layer. The control plane includes a resource allocation algorithm to optimally assign optical splitters to the flows. The hardware architecture is built on a hybrid network with both Electronic Packet Switching (EPS) and Optical Circuit Switching (OCS) networks to aggregate Top-of-Rack switches. The OCS is also the connectivity substrate of splitters to the optical network. The optical multicast system implementation requires only commodity optical components. We built a prototype and developed a simulation environment to evaluate the performance of the system for bulk multicasting. Experimental and numerical results show simultaneous delivery of multicast flows to all receivers with steady throughput. Compared to IP multicast that is the electronic counterpart, optical multicast performs with less protocol complexity and reduced energy consumption. Compared to peer-to-peer multicast methods, it achieves at minimum an order of magnitude higher throughput for flows under 250 MB with significantly less connection overheads. Furthermore, for delivering 20 TB of data containing only 15% multicast flows, it reduces the total delivery energy consumption by 50% and improves latency by 55% compared to a data center with a sole non-blocking EPS network.

S-curve networks and an approximate method for estimating degree distributions of complex networks

Science.gov (United States)

Guo, Jin-Li

2010-12-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

S-curve networks and an approximate method for estimating degree distributions of complex networks

International Nuclear Information System (INIS)

Guo Jin-Li

2010-01-01

In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research. (general)

Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD for brain cancer

Directory of Open Access Journals (Sweden)

Ying Huang

2015-07-01

Full Text Available The rapid development of new and emerging science & technologies (NESTs brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area – nano-enabled drug delivery (NEDD. NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1 international cooperation is increasing, but networking characteristics change over time; (2 highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3 research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

MicroRNA Delivery for Regenerative Medicine

OpenAIRE

Peng, Bo; Chen, Yongming; Leong, Kam W.

2015-01-01

MicroRNA (miRNA) directs post-transcriptional regulation of a network of genes by targeting mRNA. Although relatively recent in development, many miRNAs direct differentiation of various stem cells including induced pluripotent stem cells (iPSCs), a major player in regenerative medicine. An effective and safe delivery of miRNA holds the key to translating miRNA technologies. Both viral and nonviral delivery systems have seen success in miRNA delivery, and each approach possesses advantages an...

The relationship between quality of life and methods of delivery: A systematic review and meta-analysis.

Science.gov (United States)

Rezaei, Nazanin; Tavalaee, Zahra; Sayehmiri, Kourosh; Sharifi, Nasibeh; Daliri, Salman

2018-04-01

Some physical, emotional and social changes arise in mothers during the postpartum periods which can affect the quality of life (QOL) of the mother and family. Given the importance of the quality of life in the postpartum period and its influencing factors such as method of delivery, the present study aimed at investigating the relationship between the quality of life and methods of delivery in the world, using a systematic review and meta-analysis method. The present study is a systematic review and meta-analysis on the relationship between aspects of quality of life and method of delivery in the world conducted in Persian and English language articles published by the end of 2015. For this purpose, the databases of Medlib, SID, Scopus, ISI Web of Science, PubMed, Google scholar, Irandoc, Magiran and Iranmedex were searched using key words and their compounds. The results of studies were combined using the random effects model in the meta-analysis. Heterogeneity of studies was assessed using I2 index and Cochran test and data were analyzed using STATA Version 11.1 and SPSS Version 16. Based on the results of the meta-analysis of studies, the aspect of physical functioning had the highest quality of life mean score in women with vaginal delivery: 74.37 (95% CI: 67.7-81) and mental health had the highest QOL mean score in women with cesarean delivery: 65.8 (95% CI: 62.7-69). Also, based on the time elapsed since delivery, mental health had the highest mean score in less than 1 month, 2 months and 4 months' postpartum. Physical pain had the highest mean score 6 months after giving birth, and mental functioning in 8 months after giving birth. The results of the present meta-analysis showed that the mean scores for most dimensions of quality of life in women with vaginal delivery were higher than in women with cesarean delivery.

Complex networks principles, methods and applications

CERN Document Server

Latora, Vito; Russo, Giovanni

2017-01-01

Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems and metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among the others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging presentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, ...

High-resolution method for evolving complex interface networks

Science.gov (United States)

Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-04-01

In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

Hyaluronan microgel as a potential carrier for protein sustained delivery by tailoring the crosslink network

Energy Technology Data Exchange (ETDEWEB)

Luo, Chunhong [Department of Materials Science and Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632 (China); Zhao, Jianhao, E-mail: jhzhao@jnu.edu.cn [Department of Materials Science and Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632 (China); Engineering Research Center of Artificial Organs and Materials, Ministry of Education, Guangzhou 510632 (China); Tu, Mei; Zeng, Rong; Rong, Jianhua [Department of Materials Science and Engineering, College of Science and Engineering, Jinan University, Guangzhou 510632 (China); Engineering Research Center of Artificial Organs and Materials, Ministry of Education, Guangzhou 510632 (China)

2014-03-01

Hyaluronan (HA) microgels with different crosslink network, i.e. HGPs-1, HGPs-1.5, HGPs-3, HGPs-6 and HGPs-15, were synthesized using divinyl sulfone (DVS) as the crosslinker in an inverse microemulsion system for controlling the sustained delivery of bovine serum albumin (BSA). With increasing the crosslinker content, the average particle size slightly increased from 1.9 ± 0.3 μm to 3.6 ± 0.5 μm by dynamic laser scattering analysis. However, the crosslinker content had no significant effect on the morphology of HA microgels by scanning and transmission electron microscopes. Fourier transform infrared spectroscopy and elemental analysis proved more sulfur participated in the crosslink reaction when raising the crosslinker amount. The water swelling test confirmed the increasing crosslink density with the crosslinker content by calculating the average molecular weight between two crosslink points to be 8.25 ± 2.51 × 10{sup 5}, 1.26 ± 0.43 × 10{sup 5}, 0.96 ± 0.09 × 10{sup 5}, 0.64 ± 0.03 × 10{sup 5}, and 0.11 ± 0.01 × 10{sup 5} respectively. The degradation of HA microgels by hyaluronidase slowed down by enhancing the crosslink density, only about 5% of HGPs-15 was degraded as opposed to over 90% for HGPs-1. BSA loading had no obvious influence on the surface morphology of HA microgels but seemed to induce their aggregation. The increase of crosslink density decreased the BSA loading capacity but facilitated its long-term sustained delivery. When the molar ratio of DVS to repeating unit of HA reached 3 or higher, similar delivery profiles were obtained. Among all these HA microgels, HGPs-3 was the optimal carrier for BSA sustained delivery in this system because it possessed both high BSA loading capacity and long-term delivery profile simultaneously. - Highlights: • HA microgels with different crosslink densities were prepared. • The crosslinker content had little effect on the morphology and size of HA microgels. • The crosslink density

Assessment Of The Effectiveness Of Telecommunication Delivery Among Operators Of GSM In Ekiti State.

Directory of Open Access Journals (Sweden)

Olumuyiwa Oludare Fagbohun

2017-11-01

Full Text Available Data survey on the service delivery of the three principal Global System for Mobile Communications GSM Operators in Ekiti State Nigeria was conducted with a questionnaire administered among its citizens. Three locations Ado Ekiti 7o381 5o131 Ikere Ekiti 7o301 5o141 and Aramoko Ekiti 7o431 5o31were selected. Based on the responses from various subscribers using the networks the performance analyses of the operators were assessed using the descriptive statistical method. The assessment was based on the coverage area interconnectivity call quality number of subscribers growth and other supplementary services to assist the various GSM operators know the area of weakness and improve on the quality of the service delivery. It was discovered that the users have more complaints to offer with the performance generally rated below average and a need for fast and better network optimization for needed improvements for an effective telecommunication delivery.

An Entropy-Based Network Anomaly Detection Method

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Przemysław Bereziński

2015-04-01

Full Text Available Data mining is an interdisciplinary subfield of computer science involving methods at the intersection of artificial intelligence, machine learning and statistics. One of the data mining tasks is anomaly detection which is the analysis of large quantities of data to identify items, events or observations which do not conform to an expected pattern. Anomaly detection is applicable in a variety of domains, e.g., fraud detection, fault detection, system health monitoring but this article focuses on application of anomaly detection in the field of network intrusion detection.The main goal of the article is to prove that an entropy-based approach is suitable to detect modern botnet-like malware based on anomalous patterns in network. This aim is achieved by realization of the following points: (i preparation of a concept of original entropy-based network anomaly detection method, (ii implementation of the method, (iii preparation of original dataset, (iv evaluation of the method.

An algebraic topological method for multimodal brain networks comparison

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Tiago eSimas

2015-07-01

Full Text Available Understanding brain connectivity is one of the most important issues in neuroscience. Nonetheless, connectivity data can reflect either functional relationships of brain activities or anatomical connections between brain areas. Although both representations should be related, this relationship is not straightforward. We have devised a powerful method that allows different operations between networks that share the same set of nodes, by embedding them in a common metric space, enforcing transitivity to the graph topology. Here, we apply this method to construct an aggregated network from a set of functional graphs, each one from a different subject. Once this aggregated functional network is constructed, we use again our method to compare it with the structural connectivity to identify particular brain regions that differ in both modalities (anatomical and functional. Remarkably, these brain regions include functional areas that form part of the classical resting state networks. We conclude that our method -based on the comparison of the aggregated functional network- reveals some emerging features that could not be observed when the comparison is performed with the classical averaged functional network.

Non-Viral Transfection Methods Optimized for Gene Delivery to a Lung Cancer Cell Line

Science.gov (United States)

Salimzadeh, Loghman; Jaberipour, Mansooreh; Hosseini, Ahmad; Ghaderi, Abbas

2013-01-01

Background Mehr-80 is a newly established adherent human large cell lung cancer cell line that has not been transfected until now. This study aims to define the optimal transfection conditions and effects of some critical elements for enhancing gene delivery to this cell line by utilizing different non-viral transfection Procedures. Methods In the current study, calcium phosphate (CaP), DEAE-dextran, superfect, electroporation and lipofection transfection methods were used to optimize delivery of a plasmid construct that expressed Green Fluorescent Protein (GFP). Transgene expression was detected by fluorescent microscopy and flowcytometry. Toxicities of the methods were estimated by trypan blue staining. In order to evaluate the density of the transfected gene, we used a plasmid construct that expressed the Stromal cell-Derived Factor-1 (SDF-1) gene and measured its expression by real-time PCR. Results Mean levels of GFP-expressing cells 48 hr after transfection were 8.4% (CaP), 8.2% (DEAE-dextran), 4.9% (superfect), 34.1% (electroporation), and 40.1% (lipofection). Lipofection had the highest intense SDF-1 expression of the analyzed methods. Conclusion This study has shown that the lipofection and electroporation methods were more efficient at gene delivery to Mehr-80 cells. The quantity of DNA per transfection, reagent concentration, and incubation time were identified as essential factors for successful transfection in all of the studied methods. PMID:23799175

Geometrical methods for power network analysis

Energy Technology Data Exchange (ETDEWEB)

Bellucci, Stefano; Tiwari, Bhupendra Nath [Istituto Nazioneale di Fisica Nucleare, Frascati, Rome (Italy). Lab. Nazionali di Frascati; Gupta, Neeraj [Indian Institute of Technology, Kanpur (India). Dept. of Electrical Engineering

2013-02-01

Uses advanced geometrical methods to analyse power networks. Provides a self-contained and tutorial introduction. Includes a fully worked-out example for the IEEE 5 bus system. This book is a short introduction to power system planning and operation using advanced geometrical methods. The approach is based on well-known insights and techniques developed in theoretical physics in the context of Riemannian manifolds. The proof of principle and robustness of this approach is examined in the context of the IEEE 5 bus system. This work addresses applied mathematicians, theoretical physicists and power engineers interested in novel mathematical approaches to power network theory.

A Service-Oriented Approach for Dynamic Chaining of Virtual Network Functions over Multi-Provider Software-Defined Networks

Directory of Open Access Journals (Sweden)

Barbara Martini

2016-06-01

Full Text Available Emerging technologies such as Software-Defined Networks (SDN and Network Function Virtualization (NFV promise to address cost reduction and flexibility in network operation while enabling innovative network service delivery models. However, operational network service delivery solutions still need to be developed that actually exploit these technologies, especially at the multi-provider level. Indeed, the implementation of network functions as software running over a virtualized infrastructure and provisioned on a service basis let one envisage an ecosystem of network services that are dynamically and flexibly assembled by orchestrating Virtual Network Functions even across different provider domains, thereby coping with changeable user and service requirements and context conditions. In this paper we propose an approach that adopts Service-Oriented Architecture (SOA technology-agnostic architectural guidelines in the design of a solution for orchestrating and dynamically chaining Virtual Network Functions. We discuss how SOA, NFV, and SDN may complement each other in realizing dynamic network function chaining through service composition specification, service selection, service delivery, and placement tasks. Then, we describe the architecture of a SOA-inspired NFV orchestrator, which leverages SDN-based network control capabilities to address an effective delivery of elastic chains of Virtual Network Functions. Preliminary results of prototype implementation and testing activities are also presented. The benefits for Network Service Providers are also described that derive from the adaptive network service provisioning in a multi-provider environment through the orchestration of computing and networking services to provide end users with an enhanced service experience.

Dynamic baseline detection method for power data network service

Science.gov (United States)

Chen, Wei

2017-08-01

This paper proposes a dynamic baseline Traffic detection Method which is based on the historical traffic data for the Power data network. The method uses Cisco's NetFlow acquisition tool to collect the original historical traffic data from network element at fixed intervals. This method uses three dimensions information including the communication port, time, traffic (number of bytes or number of packets) t. By filtering, removing the deviation value, calculating the dynamic baseline value, comparing the actual value with the baseline value, the method can detect whether the current network traffic is abnormal.

Evaluating Student Perceptions of Course Delivery Platforms

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Bramorski, Tom; Madan, Manu S.

2016-01-01

In this paper we evaluate effectiveness of course delivery mode on three dimensions: values, networking opportunities and learning. While students and their future employers are two important customers for the business program, we focus on the perception of students regarding the effectiveness of course delivery mode on program performance. The…

Multitask Learning-Based Security Event Forecast Methods for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Hui He

2016-01-01

Full Text Available Wireless sensor networks have strong dynamics and uncertainty, including network topological changes, node disappearance or addition, and facing various threats. First, to strengthen the detection adaptability of wireless sensor networks to various security attacks, a region similarity multitask-based security event forecast method for wireless sensor networks is proposed. This method performs topology partitioning on a large-scale sensor network and calculates the similarity degree among regional subnetworks. The trend of unknown network security events can be predicted through multitask learning of the occurrence and transmission characteristics of known network security events. Second, in case of lacking regional data, the quantitative trend of unknown regional network security events can be calculated. This study introduces a sensor network security event forecast method named Prediction Network Security Incomplete Unmarked Data (PNSIUD method to forecast missing attack data in the target region according to the known partial data in similar regions. Experimental results indicate that for an unknown security event forecast the forecast accuracy and effects of the similarity forecast algorithm are better than those of single-task learning method. At the same time, the forecast accuracy of the PNSIUD method is better than that of the traditional support vector machine method.

The impact of calcium carbonate as pore forming agent and drug entrapment method towards drug dissolution mechanism of amoxicillin trihydrate encapsulated by chitosan-methyl cellulose semi-IPN hydrogel for floating drug delivery system

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Dewantara, Fauzi; Budianto, Emil

2018-04-01

Chitosan-methyl cellulose semi-IPN hydrogel is used as floating drug delivery system, and calcium carbonate also added as pore forming agent. The hydrogel network arranged by not only using biopolymer chitosan and methyl cellulose, but also the crosslink agent that is glutaraldehyde. Amoxicillin trihydrate entrapped into the polymer network with two different method, in situ loading and post loading. Furthermore both method has been tested for drug entrapment efficiency along with drug dissolution test, and the result for drug entrapment efficiency is in situ loading method has highest value of 100%, compared to post loading method which has value only 71%. Moreover, at the final time of drug dissolution test shows in situ loading method has value of 96% for total accumulative of drug dissolution, meanwhile post loading method has 72%. The value of drug dissolution test from both method is used for analyzing drug dissolution mechanism of amoxicillin trihydrate from hydrogel network with four mathematical drug mechanism models as parameter. The polymer network encounter destructive degradation causes by acid solution which used as dissolution medium, and the level of degradation is observed with optical microscope. However the result shows that degradation of the polymer network doesn't affect drug dissolution mechanism directly. Although the pore forming agent causes the pore inside the hydrogel network create interconnection and it was quite influential to drug dissolution mechanism. Interconnected pore is observed with Scanning Electron Microscope (SEM) and shows that the amount and area of interconnected pore inside the hydrogel network is increasing as drug dissolution goes on.

Is home delivery really preferred? a mixed-methods national study in Pakistan.

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Zafar, Shamsa; Sikander, Siham; Ahmad, Ikhlaq; Ahmad, Mansoor; Parveen, Nazia; Saleem, Shumaila; Nawaz, Tayyba; Suleman, Zainab; Suleman, Nadia; ulAin, Noor; Naeem, Ayesha; Bashir, Asma

2015-11-25

Pakistan has a high maternal mortality ratio and a low rate of skilled birth attendants (SBAs). To address these two important issues, the Pakistan Maternal Newborn and Child Health (MNCH) programme launched the community midwives (CMW) initiative in 2007. CMWs are supposed to conduct deliveries at community level outside health facilities. The purpose of the current study is to document perceptions about CMWs and preferences for birthing place. A mixed-methods study was conducted covering four provinces. For the quantitative survey, households were selected through a multistage sampling technique from rural districts. In 1,450 rural households, preferences of respondents about CMW-conducted deliveries were recorded. Qualitative data were obtained through focus group discussions (FGDs) and in-depth interviews (IDIs) with women, community elders, CMWs, and MNCH programme personnel in the same areas where the quantitative study was carried out. In both studies, preferences and the reasons behind particular respondent preferences were recorded. Frequencies of responses were analysed for the quantitative study. Narration and quotes from various types of participants were used to present findings from FGDs and IDIs. In the quantitative study, 42% of respondents expressed a preference for birthing stations, i.e. a place where CMWs conduct deliveries; 22% preferred home deliveries. Birthing stations were favoured because of the availability of space and equipment and the proximity to women's homes. These findings were largely supported by the qualitative component, although a range of views about where a CMW should conduct deliveries were expressed. Insights into where CMWs might provide delivery services were obtained through this study. Birthing stations may be an option as a preferred location for delivery care and should be considered as part of Pakistan's national CMW programme.

Co-Designing a Collaborative Chronic Care Network (C3N) for Inflammatory Bowel Disease: Development of Methods

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Dellal, George; Peterson, Laura E; Provost, Lloyd; Gloor, Peter A; Fore, David Livingstone; Margolis, Peter A

2018-01-01

Background Our health care system fails to deliver necessary results, and incremental system improvements will not deliver needed change. Learning health systems (LHSs) are seen as a means to accelerate outcomes, improve care delivery, and further clinical research; yet, few such systems exist. We describe the process of codesigning, with all relevant stakeholders, an approach for creating a collaborative chronic care network (C3N), a peer-produced networked LHS. Objective The objective of this study was to report the methods used, with a diverse group of stakeholders, to translate the idea of a C3N to a set of actionable next steps. Methods The setting was ImproveCareNow, an improvement network for pediatric inflammatory bowel disease. In collaboration with patients and families, clinicians, researchers, social scientists, technologists, and designers, C3N leaders used a modified idealized design process to develop a design for a C3N. Results Over 100 people participated in the design process that resulted in (1) an overall concept design for the ImproveCareNow C3N, (2) a logic model for bringing about this system, and (3) 13 potential innovations likely to increase awareness and agency, make it easier to collect and share information, and to enhance collaboration that could be tested collectively to bring about the C3N. Conclusions We demonstrate methods that resulted in a design that has the potential to transform the chronic care system into an LHS. PMID:29472173

An algebra-based method for inferring gene regulatory networks.

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Vera-Licona, Paola; Jarrah, Abdul; Garcia-Puente, Luis David; McGee, John; Laubenbacher, Reinhard

2014-03-26

The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also predicting several of the

Influence of Course Delivery Method and Proctoring on Performance in Introductory Economics

OpenAIRE

Wachenheim, Cheryl J.

2011-01-01

This work was published in the Review of Agricultural Economics. See Wachenheim, C.J. 2009. Final Exam Scores in Introductory Economics Courses: Effect of Course Delivery Method and Proctoring. Review of Agricultural Economics 31(3), pp. 640-652.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: a simulation study.

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Padhi, Radhakant; Bhardhwaj, Jayender R

2009-06-01

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Social network analysis: Presenting an underused method for nursing research.

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Parnell, James Michael; Robinson, Jennifer C

2018-06-01

This paper introduces social network analysis as a versatile method with many applications in nursing research. Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars. Discussion paper. English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017. Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design. The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses. Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models. © 2018 John Wiley & Sons Ltd.

Non-viral transfection methods optimized for gene delivery to a lung cancer cell line.

Science.gov (United States)

Salimzadeh, Loghman; Jaberipour, Mansooreh; Hosseini, Ahmad; Ghaderi, Abbas

2013-04-01

Mehr-80 is a newly established adherent human large cell lung cancer cell line that has not been transfected until now. This study aims to define the optimal transfection conditions and effects of some critical elements for enhancing gene delivery to this cell line by utilizing different non-viral transfection Procedures. In the current study, calcium phosphate (CaP), DEAE-dextran, superfect, electroporation and lipofection transfection methods were used to optimize delivery of a plasmid construct that expressed Green Fluorescent Protein (GFP). Transgene expression was detected by fluorescent microscopy and flowcytometry. Toxicities of the methods were estimated by trypan blue staining. In order to evaluate the density of the transfected gene, we used a plasmid construct that expressed the Stromal cell-Derived Factor-1 (SDF-1) gene and measured its expression by real-time PCR. Mean levels of GFP-expressing cells 48 hr after transfection were 8.4% (CaP), 8.2% (DEAE-dextran), 4.9% (superfect), 34.1% (electroporation), and 40.1% (lipofection). Lipofection had the highest intense SDF-1 expression of the analyzed methods. This study has shown that the lipofection and electroporation methods were more efficient at gene delivery to Mehr-80 cells. The quantity of DNA per transfection, reagent concentration, and incubation time were identified as essential factors for successful transfection in all of the studied methods.

QoE Power-Efficient Multimedia Delivery Method for LTE-A

OpenAIRE

Mushtaq, M. Sajid; Mellouk, Abdelhamid; Augustin, Brice; Fowler, Scott

2016-01-01

The fastest growing of multimedia services overfuture wireless communication system demand more networkresources, efficient delivery of multimedia service with highusers satisfaction, and power optimization of User Equipments(UEs). The resources and power optimization are significant infuture mobile computing systems, because emerging multimediaservices consume more resources and power. The 4G standard ofLTE-A wireless system has adopted the Discontinuous Reception(DRX) method to extend and o...

Communication devices for network-hopping communications and methods of network-hopping communications

Science.gov (United States)

Buttles, John W

2013-04-23

Wireless communication devices include a software-defined radio coupled to processing circuitry. The system controller is configured to execute computer programming code. Storage media is coupled to the system controller and includes computer programming code configured to cause the system controller to configure and reconfigure the software-defined radio to operate on each of a plurality of communication networks according to a selected sequence. Methods for communicating with a wireless device and methods of wireless network-hopping are also disclosed.

Network Forensics Method Based on Evidence Graph and Vulnerability Reasoning

Directory of Open Access Journals (Sweden)

Jingsha He

2016-11-01

Full Text Available As the Internet becomes larger in scale, more complex in structure and more diversified in traffic, the number of crimes that utilize computer technologies is also increasing at a phenomenal rate. To react to the increasing number of computer crimes, the field of computer and network forensics has emerged. The general purpose of network forensics is to find malicious users or activities by gathering and dissecting firm evidences about computer crimes, e.g., hacking. However, due to the large volume of Internet traffic, not all the traffic captured and analyzed is valuable for investigation or confirmation. After analyzing some existing network forensics methods to identify common shortcomings, we propose in this paper a new network forensics method that uses a combination of network vulnerability and network evidence graph. In our proposed method, we use vulnerability evidence and reasoning algorithm to reconstruct attack scenarios and then backtrack the network packets to find the original evidences. Our proposed method can reconstruct attack scenarios effectively and then identify multi-staged attacks through evidential reasoning. Results of experiments show that the evidence graph constructed using our method is more complete and credible while possessing the reasoning capability.

Energy and round time estimation method for mobile wireless sensor networks

International Nuclear Information System (INIS)

Ismat, M.; Qureshi, R.; Imam, M.U.

2018-01-01

Clustered WSN (Wireless Sensor Networks) is a hierarchical network structure that conserves energy by distributing the task of sensing and data transfer to destination among the non-CH (Cluster-Head) and CH (Cluster Head) node in a cluster. In clustered MWSN (Mobile Wireless Sensor Network), cluster maintenance to increase at a reception at the destination during communication operation is difficult due to the movement of CHs and non-CH nodes in and out of the cluster. To conserve energy and increased data transfer to the destination, it is necessary to find the duration after which sensor node’s role should be changed from CH to non-CH and vice-versa. In this paper, we have proposed an energy independent round time scheme to identify the duration after which re-clustering procedure should be invoked for changing roles of sensor nodes as CHs and associated nodes to conserve energy and increased data delivery. This depends on the dissemination interval of the sensor nodes rather than sensor node’s energy. We have also provided a complete analytical estimate of network energy consumption with energy consumed in every phase of a around. (author)

Quartet-based methods to reconstruct phylogenetic networks.

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Yang, Jialiang; Grünewald, Stefan; Xu, Yifei; Wan, Xiu-Feng

2014-02-20

Phylogenetic networks are employed to visualize evolutionary relationships among a group of nucleotide sequences, genes or species when reticulate events like hybridization, recombination, reassortant and horizontal gene transfer are believed to be involved. In comparison to traditional distance-based methods, quartet-based methods consider more information in the reconstruction process and thus have the potential to be more accurate. We introduce QuartetSuite, which includes a set of new quartet-based methods, namely QuartetS, QuartetA, and QuartetM, to reconstruct phylogenetic networks from nucleotide sequences. We tested their performances and compared them with other popular methods on two simulated nucleotide sequence data sets: one generated from a tree topology and the other from a complicated evolutionary history containing three reticulate events. We further validated these methods to two real data sets: a bacterial data set consisting of seven concatenated genes of 36 bacterial species and an influenza data set related to recently emerging H7N9 low pathogenic avian influenza viruses in China. QuartetS, QuartetA, and QuartetM have the potential to accurately reconstruct evolutionary scenarios from simple branching trees to complicated networks containing many reticulate events. These methods could provide insights into the understanding of complicated biological evolutionary processes such as bacterial taxonomy and reassortant of influenza viruses.

A link prediction method for heterogeneous networks based on BP neural network

Science.gov (United States)

Li, Ji-chao; Zhao, Dan-ling; Ge, Bing-Feng; Yang, Ke-Wei; Chen, Ying-Wu

2018-04-01

Most real-world systems, composed of different types of objects connected via many interconnections, can be abstracted as various complex heterogeneous networks. Link prediction for heterogeneous networks is of great significance for mining missing links and reconfiguring networks according to observed information, with considerable applications in, for example, friend and location recommendations and disease-gene candidate detection. In this paper, we put forward a novel integrated framework, called MPBP (Meta-Path feature-based BP neural network model), to predict multiple types of links for heterogeneous networks. More specifically, the concept of meta-path is introduced, followed by the extraction of meta-path features for heterogeneous networks. Next, based on the extracted meta-path features, a supervised link prediction model is built with a three-layer BP neural network. Then, the solution algorithm of the proposed link prediction model is put forward to obtain predicted results by iteratively training the network. Last, numerical experiments on the dataset of examples of a gene-disease network and a combat network are conducted to verify the effectiveness and feasibility of the proposed MPBP. It shows that the MPBP with very good performance is superior to the baseline methods.

Delivery mode and intraventricular hemorrhage risk in very-low-birth-weight infants: Observational data of the German Neonatal Network.

Science.gov (United States)

Humberg, Alexander; Härtel, Christoph; Paul, Pia; Hanke, Kathrin; Bossung, Verena; Hartz, Annika; Fasel, Laura; Rausch, Tanja K; Rody, Achim; Herting, Egbert; Göpel, Wolfgang

2017-05-01

Very-low-birth-weight infants (VLBWI) are frequently delivered by cesarean section (CS). However, it is unclear at what gestational age the benefits of spontaneous delivery outweigh the perinatal risks, i.e. intraventricular hemorrhage (IVH) or death. To assess the short-term outcome of VLBWI on IVH according to mode of delivery in a population-based cohort of the German Neonatal Network (GNN). A total cohort of 2203 singleton VLBWI with a birth weight 30 weeks of gestation prevalence for IVH was not significantly different in VD and planned CS (5.3% vs. 4.4%). Our observational data demonstrate that elective cesarean section is associated with a reduced risk of IVH in preterm infants <30 weeks gestational age when presenting with preterm labor. Copyright © 2017 Elsevier B.V. All rights reserved.

Stability-Aware Geographic Routing in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Tran Dinh Hieu

2016-05-01

Full Text Available A new generation of wireless sensor networks that harvest energy from environmental sources such as solar, vibration, and thermoelectric to power sensor nodes is emerging to solve the problem of energy limitation. Based on the photo-voltaic model, this research proposes a stability-aware geographic routing for reliable data transmissions in energy-harvesting wireless sensor networks (EH-WSNs to provide a reliable routes selection method and potentially achieve an unlimited network lifetime. Specifically, the influences of link quality, represented by the estimated packet reception rate, on network performance is investigated. Simulation results show that the proposed method outperforms an energy-harvesting-aware method in terms of energy consumption, the average number of hops, and the packet delivery ratio.

Decomposition method for analysis of closed queuing networks

Directory of Open Access Journals (Sweden)

Yu. G. Nesterov

2014-01-01

Full Text Available This article deals with the method to estimate the average residence time in nodes of closed queuing networks with priorities and a wide range of conservative disciplines to be served. The method is based on a decomposition of entire closed queuing network into a set of simple basic queuing systems such as M|GI|m|N for each node. The unknown average residence times in the network nodes are interrelated through a system of nonlinear equations. The fact that there is a solution of this system has been proved. An iterative procedure based on Newton-Kantorovich method is proposed for finding the solution of such system. This procedure provides fast convergence to solution. Today possibilities of proposed method are limited by known analytical solutions for simple basic queuing systems of M|GI|m|N type.

IP over optical multicasting for large-scale video delivery

Science.gov (United States)

Jin, Yaohui; Hu, Weisheng; Sun, Weiqiang; Guo, Wei

2007-11-01

In the IPTV systems, multicasting will play a crucial role in the delivery of high-quality video services, which can significantly improve bandwidth efficiency. However, the scalability and the signal quality of current IPTV can barely compete with the existing broadcast digital TV systems since it is difficult to implement large-scale multicasting with end-to-end guaranteed quality of service (QoS) in packet-switched IP network. China 3TNet project aimed to build a high performance broadband trial network to support large-scale concurrent streaming media and interactive multimedia services. The innovative idea of 3TNet is that an automatic switched optical networks (ASON) with the capability of dynamic point-to-multipoint (P2MP) connections replaces the conventional IP multicasting network in the transport core, while the edge remains an IP multicasting network. In this paper, we will introduce the network architecture and discuss challenges in such IP over Optical multicasting for video delivery.

Hybrid recommendation methods in complex networks.

Science.gov (United States)

Fiasconaro, A; Tumminello, M; Nicosia, V; Latora, V; Mantegna, R N

2015-07-01

We propose two recommendation methods, based on the appropriate normalization of already existing similarity measures, and on the convex combination of the recommendation scores derived from similarity between users and between objects. We validate the proposed measures on three data sets, and we compare the performance of our methods to other recommendation systems recently proposed in the literature. We show that the proposed similarity measures allow us to attain an improvement of performances of up to 20% with respect to existing nonparametric methods, and that the accuracy of a recommendation can vary widely from one specific bipartite network to another, which suggests that a careful choice of the most suitable method is highly relevant for an effective recommendation on a given system. Finally, we study how an increasing presence of random links in the network affects the recommendation scores, finding that one of the two recommendation algorithms introduced here can systematically outperform the others in noisy data sets.

Systems and methods for modeling and analyzing networks

Science.gov (United States)

Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

The effectiveness of the PRISMA integrated service delivery network: preliminary report on methods and baseline data

Directory of Open Access Journals (Sweden)

Réjean Hébert

2008-02-01

Full Text Available Purpose: The PRISMA study analyzes an innovative coordination-type integrated service delivery (ISD system developed to improve continuity and increase the effectiveness and efficiency of services, especially for older and disabled populations. The objective of the PRISMA study is to evaluate the effectiveness of this system to improve health, empowerment and satisfaction of frail older people, modify their health and social services utilization, without increasing the burden of informal caregivers. The objective of this paper is to present the methodology and give baseline data on the study participants. Methods: A quasi-experimental study with pre-test, multiple post-tests, and a comparison group was used to evaluate the impact of PRISMA ISD. Elders at risk of functional decline (501 experimental, 419 control participated in the study. Results: At entry, the two groups were comparable for most variables. Over the first year, when the implementation rate was low (32%, participants from the control group used fewer services than those from the experimental group. After the first year, no significant statistical difference was observed for functional decline and changes in the other outcome variables. Conclusion: This first year must be considered a baseline year, showing the situation without significant implementation of PRISMA ISD systems. Results for the following years will have to be examined with consideration of these baseline results.

Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

Science.gov (United States)

Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

2017-10-06

Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

NQAR: Network Quality Aware Routing in Error-Prone Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jaewon Choi

2010-01-01

Full Text Available We propose a network quality aware routing (NQAR mechanism to provide an enabling method of the delay-sensitive data delivery over error-prone wireless sensor networks. Unlike the existing routing methods that select routes with the shortest arrival latency or the minimum hop count, the proposed scheme adaptively selects the route based on the network qualities including link errors and collisions with minimum additional complexity. It is designed to avoid the paths with potential noise and collision that may cause many non-deterministic backoffs and retransmissions. We propose a generic framework to select a minimum cost route that takes the packet loss rate and collision history into account. NQAR uses a data centric approach to estimate a single-hop delay based on processing time, propagation delay, packet loss rate, number of backoffs, and the retransmission timeout between two neighboring nodes. This enables a source node to choose the shortest expected end-to-end delay path to send a delay-sensitive data. The experiment results show that NQAR reduces the end-to-end transfer delay up to approximately 50% in comparison with the latency-based directed diffusion and the hop count-based directed diffusion under the error-prone network environments. Moreover, NQAR shows better performance than those routing methods in terms of jitter, reachability, and network lifetime.

Application of social network analysis in the assessment of organization infrastructure for service delivery: a three district case study from post-conflict northern Uganda.

Science.gov (United States)

Ssengooba, Freddie; Kawooya, Vincent; Namakula, Justine; Fustukian, Suzanne

2017-10-01

In post-conflict settings, service coverage indices are unlikely to be sustained if health systems are built on weak and unstable inter-organization networks-here referred to as infrastructure. The objective of this study was to assess the inter-organization infrastructure that supports the provision of selected health services in the reconstruction phase after conflict in northern Uganda. Applied social network analysis was used to establish the structure, size and function among organizations supporting the provision of (1) HIV treatment, (2) maternal delivery services and (3) workforce strengthening. Overall, 87 organizations were identified from 48 respondent organizations in the three post-conflict districts in northern Uganda. A two-stage snowball approach was used starting with service provider organizations in each district. Data included a list of organizations and their key attributes related to the provision of each service for the year 2012-13. The findings show that inter-organization networks are mostly focused on HIV treatment and least for workforce strengthening. The networks for HIV treatment and maternal services were about 3-4 times denser relative to the network for workforce strengthening. The network for HIV treatment accounted for 69-81% of the aggregated network in Gulu and Kitgum districts. In contrast, the network for workforce strengthening contributed the least (6% and 10%) in these two districts. Likewise, the networks supporting a young district (Amuru) was under invested with few organizations and sparse connections. Overall, organizations exhibited a broad range of functional roles in supporting HIV treatment compared to other services in the study. Basic information about the inter-organization setup (infrastructure)-can contribute to knowledge for building organization networks in more equitable ways. More connected organizations can be leveraged for faster communication and resource flow to boost the delivery of health services

Wireless Sensor Network Quality of Service Improvement on Flooding Attack Condition

Science.gov (United States)

Hartono, R.; Widyawan; Wibowo, S. B.; Purnomo, A.; Hartatik

2018-03-01

There are two methods of building communication using wireless media. The first method is building a base infrastructure as an intermediary between users. Problems that arise on this type of network infrastructure is limited space to build any network physical infrastructure and also the cost factor. The second method is to build an ad hoc network between users who will communicate. On ad hoc network, each user must be willing to send data from source to destination for the occurrence of a communication. One of network protocol in Ad Hoc, Ad hoc on demand Distance Vector (AODV), has the smallest overhead value, easier to adapt to dynamic network and has small control message. One AODV protocol’s drawback is route finding process’ security for sending the data. In this research, AODV protocol is optimized by determining Expanding Ring Search (ERS) best value. Random topology is used with variation in the number of nodes: 25, 50, 75, 100, 125 and 150 with node’s speed of 10m/s in the area of 1000m x 1000m on flooding network condition. Parameters measured are Throughput, Packet Delivery Ratio, Average Delay and Normalized Routing Load. From the test results of AODV protocol optimization with best value of Expanding Ring Search (ERS), throughput increased by 5.67%, packet delivery ratio increased by 5.73%, and as for Normalized Routing Load decreased by 4.66%. ERS optimal value for each node’s condition depending on the number of nodes on the network.

Computational Experiment Study on Selection Mechanism of Project Delivery Method Based on Complex Factors

Directory of Open Access Journals (Sweden)

Xiang Ding

2014-01-01

Full Text Available Project delivery planning is a key stage used by the project owner (or project investor for organizing design, construction, and other operations in a construction project. The main task in this stage is to select an appropriate project delivery method. In order to analyze different factors affecting the PDM selection, this paper establishes a multiagent model mainly to show how project complexity, governance strength, and market environment affect the project owner’s decision on PDM. Experiment results show that project owner usually choose Design-Build method when the project is very complex within a certain range. Besides, this paper points out that Design-Build method will be the prior choice when the potential contractors develop quickly. This paper provides the owners with methods and suggestions in terms of showing how the factors affect PDM selection, and it may improve the project performance.

Testing a model of facilitated reflection on network feedback: a mixed method study on integration of rural mental healthcare services for older people.

Science.gov (United States)

Fuller, Jeffrey; Oster, Candice; Muir Cochrane, Eimear; Dawson, Suzanne; Lawn, Sharon; Henderson, Julie; O'Kane, Deb; Gerace, Adam; McPhail, Ruth; Sparkes, Deb; Fuller, Michelle; Reed, Richard L

2015-11-11

To test a management model of facilitated reflection on network feedback as a means to engage services in problem solving the delivery of integrated primary mental healthcare to older people. Participatory mixed methods case study evaluating the impact of a network management model using organisational network feedback (through social network analysis, key informant interviews and policy review). A model of facilitated network reflection using network theory and methods. A rural community in South Australia. 32 staff from 24 services and 12 senior service managers from mental health, primary care and social care services. Health and social care organisations identified that they operated in clustered self-managed networks within sectors, with no overarching purposive older people's mental healthcare network. The model of facilitated reflection revealed service goal and role conflicts. These discussions helped local services to identify as a network, and begin the problem-solving communication and referral links. A Governance Group assisted this process. Barriers to integrated servicing through a network included service funding tied to performance of direct care tasks and the lack of a clear lead network administration organisation. A model of facilitated reflection helped organisations to identify as a network, but revealed sensitivity about organisational roles and goals, which demonstrated that conflict should be expected. Networked servicing needed a neutral network administration organisation with cross-sectoral credibility, a mandate and the resources to monitor the network, to deal with conflict, negotiate commitment among the service managers, and provide opportunities for different sectors to meet and problem solve. This requires consistency and sustained intersectoral policies that include strategies and funding to facilitate and maintain health and social care networks in rural communities. Published by the BMJ Publishing Group Limited. For permission to

Quartet-net: a quartet-based method to reconstruct phylogenetic networks.

Science.gov (United States)

Yang, Jialiang; Grünewald, Stefan; Wan, Xiu-Feng

2013-05-01

Phylogenetic networks can model reticulate evolutionary events such as hybridization, recombination, and horizontal gene transfer. However, reconstructing such networks is not trivial. Popular character-based methods are computationally inefficient, whereas distance-based methods cannot guarantee reconstruction accuracy because pairwise genetic distances only reflect partial information about a reticulate phylogeny. To balance accuracy and computational efficiency, here we introduce a quartet-based method to construct a phylogenetic network from a multiple sequence alignment. Unlike distances that only reflect the relationship between a pair of taxa, quartets contain information on the relationships among four taxa; these quartets provide adequate capacity to infer a more accurate phylogenetic network. In applications to simulated and biological data sets, we demonstrate that this novel method is robust and effective in reconstructing reticulate evolutionary events and it has the potential to infer more accurate phylogenetic distances than other conventional phylogenetic network construction methods such as Neighbor-Joining, Neighbor-Net, and Split Decomposition. This method can be used in constructing phylogenetic networks from simple evolutionary events involving a few reticulate events to complex evolutionary histories involving a large number of reticulate events. A software called "Quartet-Net" is implemented and available at http://sysbio.cvm.msstate.edu/QuartetNet/.

An evaluation of gating window size, delivery method, and composite field dosimetry of respiratory-gated IMRT

International Nuclear Information System (INIS)

Hugo, Geoffrey D.; Agazaryan, Nzhde; Solberg, Timothy D.

2002-01-01

A respiratory gating system has been developed based on a commercial patient positioning system. The purpose of this study is to investigate the ability of the gating system to reproduce normal, nongated IMRT operation and to quantify the errors produced by delivering a nongated IMRT treatment onto a moving target. A moving phantom capable of simultaneous two-dimensional motion was built, and an analytical liver motion function was used to drive the phantom. Studies were performed to assess the effect of gating window size and choice of delivery method (segmented and dynamic multileaf collimation). Additionally, two multiple field IMRT cases were delivered to quantify the error in gated and nongated IMRT with motion. Dosimetric error between nonmoving and moving deliveries is related to gating window size. By reducing the window size, the error can be reduced. Delivery error can be reduced for both dynamic and segmented delivery with gating. For the implementation of dynamic IMRT delivery in this study, dynamic delivery was found to generate larger delivery errors than segmented delivery in most cases studied. For multiple field IMRT delivery, the largest errors were generated in regions where high field modulation was present parallel to the axis of motion. Gating was found to reduce these large errors to clinically acceptable levels

Information loss method to measure node similarity in networks

Science.gov (United States)

Li, Yongli; Luo, Peng; Wu, Chong

2014-09-01

Similarity measurement for the network node has been paid increasing attention in the field of statistical physics. In this paper, we propose an entropy-based information loss method to measure the node similarity. The whole model is established based on this idea that less information loss is caused by seeing two more similar nodes as the same. The proposed new method has relatively low algorithm complexity, making it less time-consuming and more efficient to deal with the large scale real-world network. In order to clarify its availability and accuracy, this new approach was compared with some other selected approaches on two artificial examples and synthetic networks. Furthermore, the proposed method is also successfully applied to predict the network evolution and predict the unknown nodes' attributions in the two application examples.

Social network extraction based on Web: 1. Related superficial methods

Science.gov (United States)

Khairuddin Matyuso Nasution, Mahyuddin

2018-01-01

Often the nature of something affects methods to resolve the related issues about it. Likewise, methods to extract social networks from the Web, but involve the structured data types differently. This paper reveals several methods of social network extraction from the same sources that is Web: the basic superficial method, the underlying superficial method, the description superficial method, and the related superficial methods. In complexity we derive the inequalities between methods and so are their computations. In this case, we find that different results from the same tools make the difference from the more complex to the simpler: Extraction of social network by involving co-occurrence is more complex than using occurrences.

Method for assessing reliability of a network considering probabilistic safety assessment

International Nuclear Information System (INIS)

Cepin, M.

2005-01-01

A method for assessment of reliability of the network is developed, which uses the features of the fault tree analysis. The method is developed in a way that the increase of the network under consideration does not require significant increase of the model. The method is applied to small examples of network consisting of a small number of nodes and a small number of their connections. The results give the network reliability. They identify equipment, which is to be carefully maintained in order that the network reliability is not reduced, and equipment, which is a candidate for redundancy, as this would improve network reliability significantly. (author)

A novel method for sub-arc VMAT dose delivery verification based on portal dosimetry with an EPID.

Science.gov (United States)

Cools, Ruud A M; Dirkx, Maarten L P; Heijmen, Ben J M

2017-11-01

The EPID-based sub-arc verification of VMAT dose delivery requires synchronization of the acquired electronic portal images (EPIs) with the VMAT delivery, that is, establishment of the start- and stop-MU of the acquired images. To realize this, published synchronization methods propose the use of logging features of the linac or dedicated hardware solutions. In this study, we developed a novel, software-based synchronization method that only uses information inherently available in the acquired images. The EPIs are continuously acquired during pretreatment VMAT delivery and converted into Portal Dose Images (PDIs). Sub-arcs of approximately 10 MU are then defined by combining groups of sequentially acquired PDIs. The start- and stop-MUs of measured sub-arcs are established in a synchronization procedure, using only dosimetric information in measured and predicted PDIs. Sub-arc verification of a VMAT dose delivery is based on comparison of measured sub-arc PDIs with synchronized, predicted sub-arc PDIs, using γ-analyses. To assess the accuracy of this new method, measured and predicted PDIs were compared for 20 clinically applied VMAT prostate cancer plans. The sensitivity of the method for detection of delivery errors was investigated using VMAT deliveries with intentionally inserted, small perturbations (25 error scenarios; leaf gap deviations ≤ 1.5 mm, leaf motion stops during ≤ 15 MU, linac output error ≤ 2%). For the 20 plans, the average failed pixel rates (FPR) for full-arc and sub-arc dose QA were 0.36% ± 0.26% (1 SD) and 0.64% ± 0.88%, based on 2%/2 mm and 3%/3 mm γ-analyses, respectively. Small systematic perturbations of up to 1% output error and 1 mm leaf offset were detected using full-arc QA. Sub-arc QA was able to detect positioning errors in three leaves only during approximately 20 MU and small dose delivery errors during approximately 40 MU. In an ROC analysis, the area under the curve (AUC) for the combined full-arc/sub-arc approach was

MRI in ocular drug delivery

OpenAIRE

Li, S. Kevin; Lizak, Martin J.; Jeong, Eun-Kee

2008-01-01

Conventional pharmacokinetic methods for studying ocular drug delivery are invasive and cannot be conveniently applied to humans. The advancement of MRI technology has provided new opportunities in ocular drug-delivery research. MRI provides a means to non-invasively and continuously monitor ocular drug-delivery systems with a contrast agent or compound labeled with a contrast agent. It is a useful technique in pharmacokinetic studies, evaluation of drug-delivery methods, and drug-delivery de...

Wireless Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Hong-Chuan Yang

2007-01-01

Full Text Available We study the energy-efficient configuration of multihop paths with automatic repeat request (ARQ mechanism in wireless ad hoc networks. We adopt a cross-layer design approach and take both the quality of each radio hop and the battery capacity of each transmitting node into consideration. Under certain constraints on the maximum tolerable transmission delay and the required packet delivery ratio, we solve optimization problems to jointly schedule the transmitting power of each transmitting node and the retransmission limit over each hop. Numerical results demonstrate that the path configuration methods can either significantly reduce the average energy consumption per packet delivery or considerably extend the average lifetime of the multihop route.

Acute and Impaired Wound Healing: Pathophysiology and Current Methods for Drug Delivery, Part 2: Role of Growth Factors in Normal and Pathological Wound Healing: Therapeutic Potential and Methods of Delivery

Science.gov (United States)

Demidova-Rice, Tatiana N.; Hamblin, Michael R.; Herman, Ira M.

2012-01-01

This is the second of 2 articles that discuss the biology and pathophysiology of wound healing, reviewing the role that growth factors play in this process and describing the current methods for growth factor delivery into the wound bed. PMID:22820962

Safe Active Scanning for Energy Delivery Systems Final Report

Energy Technology Data Exchange (ETDEWEB)

Helms, J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Salazar, B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Scheibel, P. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Engels, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Reiger, C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2017-09-30

The Department of Energy’s Cybersecurity for Energy Delivery Systems Program has funded Safe(r) Active Scanning for Energy Delivery Systems, led by Lawrence Livermore National Laboratory, to investigate and analyze the impacts of active scanning in the operational environment of energy delivery systems. In collaboration with Pacific Northwest National Laboratory and Idaho National Laboratory, active scans across three testbeds including 38 devices were performed. This report gives a summary of the initial literature survey performed on the SASEDS project as well as industry partner interview summaries and main findings from Phase 1 of the project. Additionally, the report goes into the details of scanning techniques, methodologies for testing, testbed descriptions, and scanning results, with appendices to elaborate on the specific scans that were performed. As a result of testing, a single device out of 38 exhibited problems when actively scanned, and a reboot was required to fix it. This single failure indicates that active scanning is not likely to have a detrimental effect on the safety and resilience of energy delivery systems. We provide a path forward for future research that could enable wide adoption of active scanning and lead utilities to incorporate active scanning as part of their default network security plans to discover and rectify rogue devices, adversaries, and services that may be on the network. This increased network visibility will allow operational technology cybersecurity practitioners to improve their situational awareness of networks and their vulnerabilities.

Community Based Networks and 5G

DEFF Research Database (Denmark)

Williams, Idongesit

2016-01-01

The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....

Assessment of the coordination of integrated health service delivery networks by the primary health care: COPAS questionnaire validation in the Brazilian context.

Science.gov (United States)

Rodrigues, Ludmila Barbosa Bandeira; Dos Santos, Claudia Benedita; Goyatá, Sueli Leiko Takamatsu; Popolin, Marcela Paschoal; Yamamura, Mellina; Deon, Keila Christiane; Lapão, Luis Miguel Veles; Santos Neto, Marcelino; Uchoa, Severina Alice da Costa; Arcêncio, Ricardo Alexandre

2015-07-22

Health systems organized as networks and coordinated by the Primary Health Care (PHC) may contribute to the improvement of clinical care, sanitary conditions, satisfaction of patients and reduction of local budget expenditures. The aim of this study was to adapt and validate a questionnaire - COPAS - to assess the coordination of Integrated Health Service Delivery Networks by the Primary Health Care. A cross sectional approach was used. The population was pooled from Family Health Strategy healthcare professionals, of the Alfenas region (Minas Gerais, Brazil). Data collection was performed from August to October 2013. The results were checked for the presence of floor and ceiling effects and the internal consistency measured through Cronbach alpha. Construct validity was verified through convergent and discriminant values following Multitrait-Multimethod (MTMM) analysis. Floor and ceiling effects were absent. The internal consistency of the instrument was satisfactory; as was the convergent validity, with a few correlations lower then 0.30. The discriminant validity values of the majority of items, with respect to their own dimension, were found to be higher or significantly higher than their correlations with the dimensions to which they did not belong. The results showed that the COPAS instrument has satisfactory initial psychometric properties and may be used by healthcare managers and workers to assess the PHC coordination performance within the Integrated Health Service Delivery Network.

FastStats: Births -- Method of Delivery

Science.gov (United States)

... 1990–2013 [PDF – 423 KB] Primary Cesarean Delivery Rates, by State: Results From the Revised Birth Certificate, 2006–2012 [PDF – 274 KB] Related Links Vital Statistics downloadable public use data files American College of ...

Approximation methods for the stability analysis of complete synchronization on duplex networks

Science.gov (United States)

Han, Wenchen; Yang, Junzhong

2018-01-01

Recently, the synchronization on multi-layer networks has drawn a lot of attention. In this work, we study the stability of the complete synchronization on duplex networks. We investigate effects of coupling function on the complete synchronization on duplex networks. We propose two approximation methods to deal with the stability of the complete synchronization on duplex networks. In the first method, we introduce a modified master stability function and, in the second method, we only take into consideration the contributions of a few most unstable transverse modes to the stability of the complete synchronization. We find that both methods work well for predicting the stability of the complete synchronization for small networks. For large networks, the second method still works pretty well.

An introduction to neural network methods for differential equations

CERN Document Server

Yadav, Neha; Kumar, Manoj

2015-01-01

This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks, and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed...

Social Network Analysis Applied to a Historical Ethnographic Study Surrounding Home Birth

Directory of Open Access Journals (Sweden)

Elena Andina-Diaz

2018-04-01

Full Text Available Safety during birth has improved since hospital delivery became standard practice, but the process has also become increasingly medicalised. Hence, recent years have witnessed a growing interest in home births due to the advantages it offers to mothers and their newborn infants. The aims of the present study were to confirm the transition from a home birth model of care to a scenario in which deliveries began to occur almost exclusively in a hospital setting; to define the social networks surrounding home births; and to determine whether geography exerted any influence on the social networks surrounding home births. Adopting a qualitative approach, we recruited 19 women who had given birth at home in the mid 20th century in a rural area in Spain. We employed a social network analysis method. Our results revealed three essential aspects that remain relevant today: the importance of health professionals in home delivery care, the importance of the mother’s primary network, and the influence of the geographical location of the actors involved in childbirth. All of these factors must be taken into consideration when developing strategies for maternal health.

Social Network Analysis Applied to a Historical Ethnographic Study Surrounding Home Birth.

Science.gov (United States)

Andina-Diaz, Elena; Ovalle-Perandones, Mª Antonia; Ramos-Vidal, Ignacio; Camacho-Morell, Francisca; Siles-Gonzalez, Jose; Marques-Sanchez, Pilar

2018-04-24

Safety during birth has improved since hospital delivery became standard practice, but the process has also become increasingly medicalised. Hence, recent years have witnessed a growing interest in home births due to the advantages it offers to mothers and their newborn infants. The aims of the present study were to confirm the transition from a home birth model of care to a scenario in which deliveries began to occur almost exclusively in a hospital setting; to define the social networks surrounding home births; and to determine whether geography exerted any influence on the social networks surrounding home births. Adopting a qualitative approach, we recruited 19 women who had given birth at home in the mid 20th century in a rural area in Spain. We employed a social network analysis method. Our results revealed three essential aspects that remain relevant today: the importance of health professionals in home delivery care, the importance of the mother’s primary network, and the influence of the geographical location of the actors involved in childbirth. All of these factors must be taken into consideration when developing strategies for maternal health.

A modified method of planning and delivery for dynamic multileaf collimator intensity-modulated radiation therapy

International Nuclear Information System (INIS)

Dogan, Nesrin; Leybovich, Leonid B.; Sethi, Anil; Krasin, Matthew; Emami, Bahman

2000-01-01

Purpose: To develop a modified planning and delivery technique that reduces dose nonuniformity for tomographic delivery of intensity-modulated radiation therapy (IMRT). Methods and Materials: The NOMOS-CORVUS system delivers IMRT in a tomographic paradigm. This type of delivery is prone to create multiple dose nonuniformity regions at the arc abutment regions. The modified technique was based on the cyclical behavior of arc positions as a function of a target length. With the modified technique, two plans are developed for the same patient, one with the original target and the second with a slightly increased target length and the abutment regions shifted by ∼5 mm compared to the first plan. Each plan is designed to deliver half of the target prescription dose delivered on alternate days, resulting in periodic shifts of abutment regions. This method was experimentally tested in phantoms with and without intentionally introduced errors in couch indexing. Results: With the modified technique, the degree of dose nonuniformity was reduced. For example, with 1 mm error in couch indexing, the degree of dose nonuniformity changed from ∼25% to ∼12%. Conclusion: Use of the modified technique reduces dose nonuniformity due to periodic shifts of abutment regions during treatment delivery

Determining the Effectiveness of Various Delivery Methods in an Information Technology/Information Systems Curriculum

Science.gov (United States)

Davis, Gary Alan; Kovacs, Paul J.; Scarpino, John; Turchek, John C.

2010-01-01

The emergence of increasingly sophisticated communication technologies and the media-rich extensions of the World Wide Web have prompted universities to use alternatives to the traditional classroom teaching and learning methods. This demand for alternative delivery methods has led to the development of a wide range of eLearning techniques.…

Is home delivery really preferred? a mixed-methods national study in Pakistan

OpenAIRE

Zafar, Shamsa; Sikander, Siham; Ahmad, Ikhlaq; Ahmad, Mansoor; Parveen, Nazia; Saleem, Shumaila; Nawaz, Tayyba; Suleman, Zainab; Suleman, Nadia; ulAin, Noor; Naeem, Ayesha; Bashir, Asma

2015-01-01

Background Pakistan has a high maternal mortality ratio and a low rate of skilled birth attendants (SBAs). To address these two important issues, the Pakistan Maternal Newborn and Child Health (MNCH) programme launched the community midwives (CMW) initiative in 2007. CMWs are supposed to conduct deliveries at community level outside health facilities. The purpose of the current study is to document perceptions about CMWs and preferences for birthing place. Methods A mixed-methods study was co...

Synthesis of PLGA-Lipid Hybrid Nanoparticles for siRNA Delivery Using the Emulsion Method PLGA-PEG-Lipid Nanoparticles for siRNA Delivery.

Science.gov (United States)

Wang, Lei; Griffel, Benjamin; Xu, Xiaoyang

2017-01-01

The effective delivery of small interfering RNA (siRNA) to tumor cells remains a challenge for applications in cancer therapy. The development of polymeric nanoparticles with high siRNA loading efficacy has shown great potential for cancer targets. Double emulsion solvent evaporation technique is a useful tool for encapsulation of hydrophilic molecules (e.g., siRNA). Here we describe a versatile platform for siRNA delivery based on PLGA-PEG-cationic lipid nanoparticles by using the double emulsion method. The resulting nanoparticles show high encapsulation efficiency for siRNA (up to 90%) and demonstrate effective downregulation of the target genes in vitro and vivo.

Non-invasive Oil-Based Method to Increase Topical Delivery of Nucleic Acids to Skin.

Science.gov (United States)

Vij, Manika; Alam, Shamshad; Gupta, Nidhi; Gotherwal, Vishvabandhu; Gautam, Hemlata; Ansari, Kausar M; Santhiya, Deenan; Natarajan, Vivek T; Ganguli, Munia

2017-06-07

Topical delivery of nucleic acids to skin has huge prospects in developing therapeutic interventions for cutaneous disorders. In spite of initial success, clinical translation is vastly impeded by the constraints of bioavailability as well as stability in metabolically active environment of skin. Various physical and chemical methods used to overcome these limitations involve invasive procedures or compounds that compromise skin integrity. Hence, there is an increasing demand for developing safe skin penetration enhancers for efficient nucleic acid delivery to skin. Here, we demonstrate that pretreatment of skin with silicone oil can increase the transfection efficiency of non-covalently associated peptide-plasmid DNA nanocomplexes in skin ex vivo and in vivo. The method does not compromise skin integrity, as indicated by microscopic evaluation of cellular differentiation, tissue architecture, enzyme activity assessment, dye penetration tests using Franz assay, and cytotoxicity and immunogenicity analyses. Stability of nanocomplexes is not hampered on pretreatment, thereby avoiding nuclease-mediated degradation. The mechanistic insights through Fourier transform infrared (FTIR) spectroscopy reveal some alterations in the skin hydration status owing to possible occlusion effects of the enhancer. Overall, we describe a topical, non-invasive, efficient, and safe method that can be used to increase the penetration and delivery of plasmid DNA to skin for possible therapeutic applications. Copyright © 2017 The American Society of Gene and Cell Therapy. Published by Elsevier Inc. All rights reserved.

Effect of administration method, animal weight and age on the intranasal delivery of drugs to the brain.

Science.gov (United States)

Krishnan, Jishnu K S; Arun, Peethambaran; Chembukave, Bhadra; Appu, Abhilash P; Vijayakumar, Nivetha; Moffett, John R; Puthillathu, Narayanan; Namboodiri, Aryan M A

2017-07-15

The intranasal route of administration has proven to be an effective method for bypassing the blood brain barrier and avoiding first pass hepatic metabolism when targeting drugs to the brain. Most small molecules gain rapid access to CNS parenchyma when administered intranasally. However, bioavailability is affected by various factors ranging from the molecular weight of the drug to the mode of intranasal delivery. We examined the effects of animal posture, intranasal application method and animal weight and age on the delivery of radiolabeled pralidoxime ( 3 H-2-PAM) to the brain of rats. We found that using upright vs. supine posture did not significantly affect 3 H-2-PAM concentrations in different brain regions. Older animals with higher weights required increased doses to achieve the same drug concentration throughout the brain when compared to young animals with lower body weights. The use of an intranasal aerosol propelled delivery device mainly increased bioavailability in the olfactory bulbs, but did not reliably increase delivery of the drug to various other brain regions, and in some regions of the brain delivered less of the drug than simple pipette administration. In view of the emerging interest in the use of intranasal delivery of drugs to combat cognitive decline in old age, we tested effectiveness in very old rats and found the method to be as effective in the older rats. Copyright © 2017 Elsevier B.V. All rights reserved.

New Method for Leakage Detection by Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Mohammad Attari

2018-03-01

Full Text Available Nowadays water loss has been turned into a global concern and on the other hand the demand for water is increasing. This problem has made the demand management and consumption pattern reform necessary. One of the most important methods for managing water consumption is to decrease the water loss. In this study by using neural networks, a new method is presented to specify the location and quantity of leakages in water distribution networks.  In this method, by producing the training data and applying it to neural network, the network is able to determine approximate location and quantity of nodal leakage with receiving the nodal pressure. Production of training data is carried out by applying assumed leakage to specific nodes in the network and calculating the new nodal pressures. The results show that by minimum use of hydraulic data taken from pressures, not only this method can determine the location of nodal leakages, but also it can specify the amount of leakage on each node with reasonable accuracy.

Control of beam halo-chaos using neural network self-adaptation method

International Nuclear Information System (INIS)

Fang Jinqing; Huang Guoxian; Luo Xiaoshu

2004-11-01

Taking the advantages of neural network control method for nonlinear complex systems, control of beam halo-chaos in the periodic focusing channels (network) of high intensity accelerators is studied by feed-forward back-propagating neural network self-adaptation method. The envelope radius of high-intensity proton beam is reached to the matching beam radius by suitably selecting the control structure of neural network and the linear feedback coefficient, adjusted the right-coefficient of neural network. The beam halo-chaos is obviously suppressed and shaking size is much largely reduced after the neural network self-adaptation control is applied. (authors)

Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

Science.gov (United States)

Stoenescu, Tudor M.; Woo, Simon S.

2009-01-01

In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

Dynamic Subsidy Method for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei

2016-01-01

Dynamic subsidy (DS) is a locational price paid by the distribution system operator (DSO) to its customers in order to shift energy consumption to designated hours and nodes. It is promising for demand side management and congestion management. This paper proposes a new DS method for congestion...... management in distribution networks, including the market mechanism, the mathematical formulation through a two-level optimization, and the method solving the optimization by tightening the constraints and linearization. Case studies were conducted with a one node system and the Bus 4 distribution network...... of the Roy Billinton Test System (RBTS) with high penetration of electric vehicles (EVs) and heat pumps (HPs). The case studies demonstrate the efficacy of the DS method for congestion management in distribution networks. Studies in this paper show that the DS method offers the customers a fair opportunity...

[Preparation of panax notoginseng saponins-tanshinone H(A) composite method for pulmonary delivery with spray-drying method and its characterization].

Science.gov (United States)

Wang, Hua-Mei; Fu, Ting-Ming; Guo, Li-Wei

2013-02-01

To prepare panax notoginseng saponins-tanshinone II(A) composite particles for pulmonary delivery, in order to explore a dry powder particle preparation method ensuring synchronized arrival of multiple components of traditional Chinese medicine compounds at absorption sites. Panax notoginseng saponins-tanshinone II(A) composite particles were prepared with spray-drying method, and characterized by scanning electron microscopy (SEM), confocal laser scanning microscope (CLSM), X-ray diffraction (XRD), infrared analysis (IR), dry laser particle size analysis, high performance liquid chromatography (HPLC) and the aerodynamic behavior was evaluated by a Next Generation Impactor (NGI). The dry powder particles produced had narrow particle size distribution range and good aerodynamic behavior, and could realize synchronized administration of multiple components. The spray-drying method is used to combine traditional Chinese medicine components with different physical and chemical properties in the same particle, and product into traditional Chinese medicine compound particles in line with the requirements for pulmonary delivery.

NDN-CRAHNs: Named Data Networking for Cognitive Radio Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Rana Asif Rehman

2015-01-01

Full Text Available Named data networking (NDN is a newly proposed paradigm for future Internet, in which communication among nodes is based on data names, decoupling from their locations. In dynamic and self-organized cognitive radio ad hoc networks (CRAHNs, it is difficult to maintain end-to-end connectivity between ad hoc nodes especially in the presence of licensed users and intermittent wireless channels. Moreover, IP-based CRAHNs have several issues like scalability, inefficient-mapping, poor resource utilization, and location dependence. By leveraging the advantages of NDN, in this paper, we propose a new cross layer fine-grained architecture called named data networking for cognitive radio ad hoc networks (NDN-CRAHNs. The proposed architecture provides distinct features such as in-networking caching, security, scalability, and multipath routing. The performances of the proposed scheme are evaluated comparing to IP-based scheme in terms of average end-to-end delay and packet delivery ratio. Simulation results show that the proposed scheme is effective in terms of average contents download time and packet delivery ratios comparing to conventional cognitive radio ad hoc networks.

Noninvasive ocular drug delivery: potential transcorneal and other alternative delivery routes for therapeutic molecules in glaucoma.

Science.gov (United States)

Foldvari, Marianna

2014-01-01

Drug delivery to the eye is made difficult by multiple barriers (such as the tear film, cornea, and vitreous) between the surface of the eye and the treatment site. These barriers are difficult to surmount for the purposes of drug delivery without causing toxicity. Using nanotechnology tools to control, manipulate, and study delivery systems, new approaches to delivering drugs, genes, and antigens that are effective and safe can be developed. Topical administration to the ocular surface would be the safest method for delivery, as it is noninvasive and painless compared with other delivery methods. However, there is only limited success using topical delivery methods, especially for gene therapy. Current thinking on treatments of the future enabled by nanodelivery systems and the identification of target specificity parameters that require deeper understanding to develop successful topical delivery systems for glaucoma is highlighted.

Development of a general method for obtaining the geometry of microfluidic networks

International Nuclear Information System (INIS)

Razavi, Mohammad Sayed; Salimpour, M. R.; Shirani, Ebrahim

2014-01-01

In the present study, a general method for geometry of fluidic networks is developed with emphasis on pressure-driven flows in the microfluidic applications. The design method is based on general features of network's geometry such as cross-sectional area and length of channels. Also, the method is applicable to various cross-sectional shapes such as circular, rectangular, triangular, and trapezoidal cross sections. Using constructal theory, the flow resistance, energy loss and performance of the network are optimized. Also, by this method, practical design strategies for the fabrication of microfluidic networks can be improved. The design method enables rapid prediction of fluid flow in the complex network of channels and is very useful for improving proper miniaturization and integration of microfluidic networks. Minimization of flow resistance of the network of channels leads to universal constants for consecutive cross-sectional areas and lengths. For a Y-shaped network, the optimal ratios of consecutive cross-section areas (A i+1 /A i ) and lengths (L i+1 /L i ) are obtained as A i+1 /A i = 2 −2/3 and L i+1 /L i = 2 −1/3 , respectively. It is shown that energy loss in the network is proportional to the volume of network. It is also seen when the number of channels is increased both the hydraulic resistance and the volume occupied by the network are increased in a similar manner. Furthermore, the method offers that fabrication of multi-depth and multi-width microchannels should be considered as an integral part of designing procedures. Finally, numerical simulations for the fluid flow in the network have been performed and results show very good agreement with analytic results

Electrochemical Detection in Stacked Paper Networks.

Science.gov (United States)

Liu, Xiyuan; Lillehoj, Peter B

2015-08-01

Paper-based electrochemical biosensors are a promising technology that enables rapid, quantitative measurements on an inexpensive platform. However, the control of liquids in paper networks is generally limited to a single sample delivery step. Here, we propose a simple method to automate the loading and delivery of liquid samples to sensing electrodes on paper networks by stacking multiple layers of paper. Using these stacked paper devices (SPDs), we demonstrate a unique strategy to fully immerse planar electrodes by aqueous liquids via capillary flow. Amperometric measurements of xanthine oxidase revealed that electrochemical sensors on four-layer SPDs generated detection signals up to 75% higher compared with those on single-layer paper devices. Furthermore, measurements could be performed with minimal user involvement and completed within 30 min. Due to its simplicity, enhanced automation, and capability for quantitative measurements, stacked paper electrochemical biosensors can be useful tools for point-of-care testing in resource-limited settings. © 2015 Society for Laboratory Automation and Screening.

Inequity in ecosystem service delivery: Socioeconomic gaps in the public-private conservation network

Science.gov (United States)

Villamagna, Amy M.; Mogollón, Beatriz; Angermeier, Paul L.

2017-01-01

private conservation lands included beneficiaries of significantly greater household income than benefit zones of other types of conservation areas. Our analysis of ES flows revealed significant socioeconomic gaps in how the current public-private conservation network benefits the public. These gaps warrant consideration in regional conservation plans and suggest that private conservation initiatives may be best suited for responding to the equity challenge. Enhancing the ecosystem benefits and the equity of benefit delivery from private conservation networks could build public and political support for long-term conservation strategies and ultimately enhance conservation efficacy.

Social network extraction based on Web: 3. the integrated superficial method

Science.gov (United States)

Nasution, M. K. M.; Sitompul, O. S.; Noah, S. A.

2018-03-01

The Web as a source of information has become part of the social behavior information. Although, by involving only the limitation of information disclosed by search engines in the form of: hit counts, snippets, and URL addresses of web pages, the integrated extraction method produces a social network not only trusted but enriched. Unintegrated extraction methods may produce social networks without explanation, resulting in poor supplemental information, or resulting in a social network of durmise laden, consequently unrepresentative social structures. The integrated superficial method in addition to generating the core social network, also generates an expanded network so as to reach the scope of relation clues, or number of edges computationally almost similar to n(n - 1)/2 for n social actors.

The Multi-commodity One-to-one Pickup-and-delivery Traveling Salesman Problem with Path Duration Limits

DEFF Research Database (Denmark)

Plum, Christian Edinger Munk; Pisinger, David; Salazar-González, Juan-José

2012-01-01

The design of container shipping networks is an important real world problem, with assets and operational costs in billions of dollars. To guide the optimal deployment of the ships, a single vessel roundtrip is considered by minimizing operational costs and flowing the best paying cargo under...... commercial constraints. Inspiration for formulation and solution method is taken from the rich research done within pickup and delivery problems. The problem, the multicommodity one-toone pickup and delivery traveling salesman problem with path duration limits is, to the best of out knowledge, considered...... for the first time. An arc flow and a path flow model are presented. A Branch and Cut and Price solution method is proposed and implemented....

Time and Frequency Transfer and Dissemination Methods Using Optical Fiber Network

National Research Council Canada - National Science Library

Amemiya, Masaki; Imae, Michito; Fuji, Yasuhisa; Suzuyama, Tomonari; Ohshima, Shin-ichi

2005-01-01

... developing. This study shows two methods using optical fiber networks to satisfy these demands. First, it is an economical remote calibration method using existing synchronous optical fiber communication networks...

Approximation methods for efficient learning of Bayesian networks

CERN Document Server

Riggelsen, C

2008-01-01

This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order to provide a coherent treatment of matters, thereby helping the reader to gain a thorough understanding of the whole concept of learning Bayesian networks from (in)complete data, this publication combines in a clarifying way all the issues presented in the papers with previously unpublished work.

A method of network topology optimization design considering application process characteristic

Science.gov (United States)

Wang, Chunlin; Huang, Ning; Bai, Yanan; Zhang, Shuo

2018-03-01

Communication networks are designed to meet the usage requirements of users for various network applications. The current studies of network topology optimization design mainly considered network traffic, which is the result of network application operation, but not a design element of communication networks. A network application is a procedure of the usage of services by users with some demanded performance requirements, and has obvious process characteristic. In this paper, we first propose a method to optimize the design of communication network topology considering the application process characteristic. Taking the minimum network delay as objective, and the cost of network design and network connective reliability as constraints, an optimization model of network topology design is formulated, and the optimal solution of network topology design is searched by Genetic Algorithm (GA). Furthermore, we investigate the influence of network topology parameter on network delay under the background of multiple process-oriented applications, which can guide the generation of initial population and then improve the efficiency of GA. Numerical simulations show the effectiveness and validity of our proposed method. Network topology optimization design considering applications can improve the reliability of applications, and provide guidance for network builders in the early stage of network design, which is of great significance in engineering practices.

[Surgical methods for delivery in modern obstetrics and their influence on maternal and infant health].

Science.gov (United States)

Kokhanevych, Ie V; Mitsoda, R M; Konoplianko, T V; Konoplianko, V V

2000-03-01

The article addresses issues of comparative characterization of deliveries involving surgery and impact thereof on the health of the mother and her child. Risk factors are identified that the mother and her child run in sectio cesarea, in application of obstetrical forceps, and in vacuum-extraction of the fetus. Cesarean section was found out to be the most acceptable mode of delivery in origination of organic and functional nervous system involvement in children but the most ill-chosen and unpropitious one in the mother, especially so in those groups at risk for bleeding, septic complications, and genital endometriosis. Among those surgical methods of delivery being the least traumatic to the mother are obstetrical forceps and vacuum-extraction of the fetus.

Optimal topologies for maximizing network transmission capacity

Science.gov (United States)

Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.

2018-04-01

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Web Page Classification Method Using Neural Networks

Science.gov (United States)

Selamat, Ali; Omatu, Sigeru; Yanagimoto, Hidekazu; Fujinaka, Toru; Yoshioka, Michifumi

Automatic categorization is the only viable method to deal with the scaling problem of the World Wide Web (WWW). In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). Each news web page is represented by the term-weighting scheme. As the number of unique words in the collection set is big, the principal component analysis (PCA) has been used to select the most relevant features for the classification. Then the final output of the PCA is combined with the feature vectors from the class-profile which contains the most regular words in each class before feeding them to the neural networks. We have manually selected the most regular words that exist in each class and weighted them using an entropy weighting scheme. The fixed number of regular words from each class will be used as a feature vectors together with the reduced principal components from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM method provides acceptable classification accuracy with the sports news datasets.

A multi-scale network method for two-phase flow in porous media

Energy Technology Data Exchange (ETDEWEB)

Khayrat, Karim, E-mail: khayratk@ifd.mavt.ethz.ch; Jenny, Patrick

2017-08-01

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

Network reliability analysis of complex systems using a non-simulation-based method

International Nuclear Information System (INIS)

Kim, Youngsuk; Kang, Won-Hee

2013-01-01

Civil infrastructures such as transportation, water supply, sewers, telecommunications, and electrical and gas networks often establish highly complex networks, due to their multiple source and distribution nodes, complex topology, and functional interdependence between network components. To understand the reliability of such complex network system under catastrophic events such as earthquakes and to provide proper emergency management actions under such situation, efficient and accurate reliability analysis methods are necessary. In this paper, a non-simulation-based network reliability analysis method is developed based on the Recursive Decomposition Algorithm (RDA) for risk assessment of generic networks whose operation is defined by the connections of multiple initial and terminal node pairs. The proposed method has two separate decomposition processes for two logical functions, intersection and union, and combinations of these processes are used for the decomposition of any general system event with multiple node pairs. The proposed method is illustrated through numerical network examples with a variety of system definitions, and is applied to a benchmark gas transmission pipe network in Memphis TN to estimate the seismic performance and functional degradation of the network under a set of earthquake scenarios.

A multi-scale network method for two-phase flow in porous media

International Nuclear Information System (INIS)

Khayrat, Karim; Jenny, Patrick

2017-01-01

Pore-network models of porous media are useful in the study of pore-scale flow in porous media. In order to extract macroscopic properties from flow simulations in pore-networks, it is crucial the networks are large enough to be considered representative elementary volumes. However, existing two-phase network flow solvers are limited to relatively small domains. For this purpose, a multi-scale pore-network (MSPN) method, which takes into account flow-rate effects and can simulate larger domains compared to existing methods, was developed. In our solution algorithm, a large pore network is partitioned into several smaller sub-networks. The algorithm to advance the fluid interfaces within each subnetwork consists of three steps. First, a global pressure problem on the network is solved approximately using the multiscale finite volume (MSFV) method. Next, the fluxes across the subnetworks are computed. Lastly, using fluxes as boundary conditions, a dynamic two-phase flow solver is used to advance the solution in time. Simulation results of drainage scenarios at different capillary numbers and unfavourable viscosity ratios are presented and used to validate the MSPN method against solutions obtained by an existing dynamic network flow solver.

Protocol and networking design issues for local access WDM networks

NARCIS (Netherlands)

Salvador, M.R.; Heemstra de Groot, S.M.; Niemegeers, I.G.M.M.

This report gives an overview of some of the protocol and networking design issues that have been addressed in Flamingo, a major ongoing project which investigates the use of WDM optical technology in local access networks. Quality of service delivery and wavelength assignment are focused on in this

Network Theory and Effects of Transcranial Brain Stimulation Methods on the Brain Networks

Directory of Open Access Journals (Sweden)

Sema Demirci

2014-12-01

Full Text Available In recent years, there has been a shift from classic localizational approaches to new approaches where the brain is considered as a complex system. Therefore, there has been an increase in the number of studies involving collaborations with other areas of neurology in order to develop methods to understand the complex systems. One of the new approaches is graphic theory that has principles based on mathematics and physics. According to this theory, the functional-anatomical connections of the brain are defined as a network. Moreover, transcranial brain stimulation techniques are amongst the recent research and treatment methods that have been commonly used in recent years. Changes that occur as a result of applying brain stimulation techniques on physiological and pathological networks help better understand the normal and abnormal functions of the brain, especially when combined with techniques such as neuroimaging and electroencephalography. This review aims to provide an overview of the applications of graphic theory and related parameters, studies conducted on brain functions in neurology and neuroscience, and applications of brain stimulation systems in the changing treatment of brain network models and treatment of pathological networks defined on the basis of this theory.

MRI-Guided Focused Ultrasound as a New Method of Drug Delivery

Directory of Open Access Journals (Sweden)

M. Thanou

2013-01-01

Full Text Available Ultrasound-mediated drug delivery under the guidance of an imaging modality can improve drug disposition and achieve site-specific drug delivery. The term focal drug delivery has been introduced to describe the focal targeting of drugs in tissues with the help of imaging and focused ultrasound. Focal drug delivery aims to improve the therapeutic profile of drugs by improving their specificity and their permeation in defined areas. Focused-ultrasound- (FUS- mediated drug delivery has been applied with various molecules to improve their local distribution in tissues. FUS is applied with the aid of microbubbles to enhance the permeability of bioactive molecules across BBB and improve drug distribution in the brain. Recently, FUS has been utilised in combination with MRI-labelled liposomes that respond to temperature increase. This strategy aims to “activate” nanoparticles to release their cargo locally when triggered by hyperthermia induced by FUS. MRI-guided FUS drug delivery provides the opportunity to improve drug bioavailability locally and therefore improve the therapeutic profiles of drugs. This drug delivery strategy can be directly translated to clinic as MRg FUS is a promising clinically therapeutic approach. However, more basic research is required to understand the physiological mechanism of FUS-enhanced drug delivery.

Identifying influential spreaders in complex networks based on kshell hybrid method

Science.gov (United States)

Namtirtha, Amrita; Dutta, Animesh; Dutta, Biswanath

2018-06-01

Influential spreaders are the key players in maximizing or controlling the spreading in a complex network. Identifying the influential spreaders using kshell decomposition method has become very popular in the recent time. In the literature, the core nodes i.e. with the largest kshell index of a network are considered as the most influential spreaders. We have studied the kshell method and spreading dynamics of nodes using Susceptible-Infected-Recovered (SIR) epidemic model to understand the behavior of influential spreaders in terms of its topological location in the network. From the study, we have found that every node in the core area is not the most influential spreader. Even a strategically placed lower shell node can also be a most influential spreader. Moreover, the core area can also be situated at the periphery of the network. The existing indexing methods are only designed to identify the most influential spreaders from core nodes and not from lower shells. In this work, we propose a kshell hybrid method to identify highly influential spreaders not only from the core but also from lower shells. The proposed method comprises the parameters such as kshell power, node's degree, contact distance, and many levels of neighbors' influence potential. The proposed method is evaluated using nine real world network datasets. In terms of the spreading dynamics, the experimental results show the superiority of the proposed method over the other existing indexing methods such as the kshell method, the neighborhood coreness centrality, the mixed degree decomposition, etc. Furthermore, the proposed method can also be applied to large-scale networks by considering the three levels of neighbors' influence potential.

Artificial neural network and classical least-squares methods for neurotransmitter mixture analysis.

Science.gov (United States)

Schulze, H G; Greek, L S; Gorzalka, B B; Bree, A V; Blades, M W; Turner, R F

1995-02-01

Identification of individual components in biological mixtures can be a difficult problem regardless of the analytical method employed. In this work, Raman spectroscopy was chosen as a prototype analytical method due to its inherent versatility and applicability to aqueous media, making it useful for the study of biological samples. Artificial neural networks (ANNs) and the classical least-squares (CLS) method were used to identify and quantify the Raman spectra of the small-molecule neurotransmitters and mixtures of such molecules. The transfer functions used by a network, as well as the architecture of a network, played an important role in the ability of the network to identify the Raman spectra of individual neurotransmitters and the Raman spectra of neurotransmitter mixtures. Specifically, networks using sigmoid and hyperbolic tangent transfer functions generalized better from the mixtures in the training data set to those in the testing data sets than networks using sine functions. Networks with connections that permit the local processing of inputs generally performed better than other networks on all the testing data sets. and better than the CLS method of curve fitting, on novel spectra of some neurotransmitters. The CLS method was found to perform well on noisy, shifted, and difference spectra.

A Method for Automated Planning of FTTH Access Network Infrastructures

DEFF Research Database (Denmark)

Riaz, Muhammad Tahir; Pedersen, Jens Myrup; Madsen, Ole Brun

2005-01-01

In this paper a method for automated planning of Fiber to the Home (FTTH) access networks is proposed. We introduced a systematic approach for planning access network infrastructure. The GIS data and a set of algorithms were employed to make the planning process more automatic. The method explains...... method. The method, however, does not fully automate the planning but make the planning process significantly fast. The results and discussion are presented and conclusion is given in the end....

A method for assessing fidelity of delivery of telephone behavioral support for smoking cessation

OpenAIRE

Lorencatto, F.; West, R.; Bruguera, C.; Michie, S.

2014-01-01

Objectives: Behavioral support for smoking cessation is delivered through different modalities, often guided by treatment manuals. Recently developed methods for assessing fidelity of delivery have shown that face-to-face behavioral support is often not delivered as specified in the service treatment manual. This study aimed to extend this method to evaluate fidelity of telephone-delivered behavioral support. \\ud \\ud Method: A treatment manual and transcripts of 75 audio-recorded behavioral s...

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

Science.gov (United States)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Diverse Delivery Methods and Strong Psychological Benefits: A Review of Online Formative Assessment

Science.gov (United States)

McLaughlin, T.; Yan, Z.

2017-01-01

This article is a review of literature on online formative assessment (OFA). It includes a narrative summary that synthesizes the research on the diverse delivery methods of OFA, as well as the empirical literature regarding the strong psychological benefits and limitations. Online formative assessment can be delivered using many traditional…

Handwritten Javanese Character Recognition Using Several Artificial Neural Network Methods

Directory of Open Access Journals (Sweden)

Gregorius Satia Budhi

2015-07-01

Full Text Available Javanese characters are traditional characters that are used to write the Javanese language. The Javanese language is a language used by many people on the island of Java, Indonesia. The use of Javanese characters is diminishing more and more because of the difficulty of studying the Javanese characters themselves. The Javanese character set consists of basic characters, numbers, complementary characters, and so on. In this research we have developed a system to recognize Javanese characters. Input for the system is a digital image containing several handwritten Javanese characters. Preprocessing and segmentation are performed on the input image to get each character. For each character, feature extraction is done using the ICZ-ZCZ method. The output from feature extraction will become input for an artificial neural network. We used several artificial neural networks, namely a bidirectional associative memory network, a counterpropagation network, an evolutionary network, a backpropagation network, and a backpropagation network combined with chi2. From the experimental results it can be seen that the combination of chi2 and backpropagation achieved better recognition accuracy than the other methods.

Dynamics of Indel Profiles Induced by Various CRISPR/Cas9 Delivery Methods

DEFF Research Database (Denmark)

Kosicki, Michael; Rajan, Sandeep S; Lorenzetti, Flaminia C

2017-01-01

The introduction of CRISPR/Cas9 gene editing in mammalian cells is a scientific breakthrough, which has greatly affected basic research and gene therapy. The simplicity and general access to CRISPR/Cas9 reagents has in an unprecedented manner "democratized" gene targeting in biomedical research...... approach. In this study we review the most commonly used indel detection methods and using a robust, sensitive, and cost efficient Indel Detection by Amplicon Analysis method, we have investigated the impact of the most commonly used CRISPR/Cas9 delivery formats, including lentivirus transduction, plasmid...

SOUNET: Self-Organized Underwater Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Hee-won Kim

2017-02-01

Full Text Available In this paper, we propose an underwater wireless sensor network (UWSN named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR, and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

SOUNET: Self-Organized Underwater Wireless Sensor Network.

Science.gov (United States)

Kim, Hee-Won; Cho, Ho-Shin

2017-02-02

In this paper, we propose an underwater wireless sensor network (UWSN) named SOUNET where sensor nodes form and maintain a tree-topological network for data gathering in a self-organized manner. After network topology discovery via packet flooding, the sensor nodes consistently update their parent node to ensure the best connectivity by referring to the timevarying neighbor tables. Such a persistent and self-adaptive method leads to high network connectivity without any centralized control, even when sensor nodes are added or unexpectedly lost. Furthermore, malfunctions that frequently happen in self-organized networks such as node isolation and closed loop are resolved in a simple way. Simulation results show that SOUNET outperforms other conventional schemes in terms of network connectivity, packet delivery ratio (PDR), and energy consumption throughout the network. In addition, we performed an experiment at the Gyeongcheon Lake in Korea using commercial underwater modems to verify that SOUNET works well in a real environment.

Neonatal outcomes and operative vaginal delivery versus cesarean delivery.

LENUS (Irish Health Repository)

Contag, Stephen A

2010-06-01

We compared outcomes for neonates with forceps-assisted, vacuum-assisted, or cesarean delivery in the second stage of labor. This is a secondary analysis of a randomized trial in laboring, low-risk, nulliparous women at >or=36 weeks\\' gestation. Neonatal outcomes after use of forceps, vacuum, and cesarean were compared among women in the second stage of labor at station +1 or below (thirds scale) for failure of descent or nonreassuring fetal status. Nine hundred ninety women were included in this analysis: 549 (55%) with an indication for delivery of failure of descent and 441 (45%) for a nonreassuring fetal status. Umbilical cord gases were available for 87% of neonates. We found no differences in the base excess (P = 0.35 and 0.78 for failure of descent and nonreassuring fetal status) or frequencies of pH below 7.0 (P = 0.73 and 0.34 for failure of descent and nonreassuring fetal status) among the three delivery methods. Birth outcomes and umbilical cord blood gas values were similar for those neonates with a forceps-assisted, vacuum-assisted, or cesarean delivery in the second stage of labor. The occurrence of significant fetal acidemia was not different among the three delivery methods regardless of the indication.

Explicit integration of extremely stiff reaction networks: partial equilibrium methods

International Nuclear Information System (INIS)

Guidry, M W; Hix, W R; Billings, J J

2013-01-01

In two preceding papers (Guidry et al 2013 Comput. Sci. Disc. 6 015001 and Guidry and Harris 2013 Comput. Sci. Disc. 6 015002), we have shown that when reaction networks are well removed from equilibrium, explicit asymptotic and quasi-steady-state approximations can give algebraically stabilized integration schemes that rival standard implicit methods in accuracy and speed for extremely stiff systems. However, we also showed that these explicit methods remain accurate but are no longer competitive in speed as the network approaches equilibrium. In this paper, we analyze this failure and show that it is associated with the presence of fast equilibration timescales that neither asymptotic nor quasi-steady-state approximations are able to remove efficiently from the numerical integration. Based on this understanding, we develop a partial equilibrium method to deal effectively with the approach to equilibrium and show that explicit asymptotic methods, combined with the new partial equilibrium methods, give an integration scheme that can plausibly deal with the stiffest networks, even in the approach to equilibrium, with accuracy and speed competitive with that of implicit methods. Thus we demonstrate that such explicit methods may offer alternatives to implicit integration of even extremely stiff systems and that these methods may permit integration of much larger networks than have been possible before in a number of fields. (paper)

Data Dissemination Based on Fuzzy Logic and Network Coding in Vehicular Networks

Directory of Open Access Journals (Sweden)

Xiaolan Tang

2017-01-01

Full Text Available Vehicular networks, as a significant technology in intelligent transportation systems, improve the convenience, efficiency, and safety of driving in smart cities. However, because of the high velocity, the frequent topology change, and the limited bandwidth, it is difficult to efficiently propagate data in vehicular networks. This paper proposes a data dissemination scheme based on fuzzy logic and network coding for vehicular networks, named SFN. It uses fuzzy logic to compute a transmission ability for each vehicle by comprehensively considering the effects of three factors: the velocity change rate, the velocity optimization degree, and the channel quality. Then, two nodes with high abilities are selected as primary backbone and slave backbone in every road segment, which propagate data to other vehicles in this segment and forward them to the backbones in the next segment. The backbone network helps to increase the delivery ratio and avoid invalid transmissions. Additionally, network coding is utilized to reduce transmission overhead and accelerate data retransmission in interbackbone forwarding and intrasegment broadcasting. Experiments show that, compared with existing schemes, SFN has a high delivery ratio and a short dissemination delay, while the backbone network keeps high reliability.

Design and Implementation of a MAC Protocol for Timely and Reliable Delivery of Command and Data in Dynamic Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Phan Van Vinh

2013-09-01

Full Text Available This paper proposes and implements a new TDMA-based MAC protocol for providing timely and reliable delivery of data and command for monitoring and control networks. In this kind of network, sensor nodes are required to sense data from the monitoring environment periodically and then send the data to a sink. The sink determines whether the environment is safe or not by analyzing the acquired data. Sometimes, a command or control message is sent from the sink to a particular node or a group of nodes to execute the services or request further interested data. The proposed MAC protocol enables bidirectional communication, controls active and sleep modes of a sensor node to conserve energy, and addresses the problem of load unbalancing between the nodes near a sink and the other nodes. It can improve reliability of communication significantly while extending network lifetime. These claims are supported by the experimental results.

Cultural perceptions and preferences of Iranian women regarding cesarean delivery

Science.gov (United States)

Latifnejad-Roudsari, Robab; Zakerihamidi, Maryam; Merghati-Khoei, Effat; Kazemnejad, Anoshirvan

2014-01-01

Background: Data was reported in Iran in 2013 has shown that almost 42 percent of deliveries in public hospitals and 90 percent in private hospitals were carried out with cesarean section. This high rate of cesarean requires careful consideration. It seems that making decision for cesarean is done under the influence of cultural perceptions and beliefs. So, this study was conducted to explore pregnant women's preferences and perceptions regarding cesarean delivery. Materials and Methods: A focused ethnographic study was used. 12 pregnant women and 10 delivered women, seven midwives, seven gynecologist and nine non-pregnant women referred to the health clinics of Tonekabon, who selected purposively, were included in the study. To collect data semi-structured in-depth interviews and participant observation were used. Study rigor was confirmed through prolonged engagement, member check, expert debriefing, and thick description of the data. Data were analysed using thematic analysis and MAXQDA software. Results: Four themes emerged from the data including personal beliefs, fear of vaginal delivery, cultural norms and values and also social network. These concepts played main roles in how women develop meanings toward caesarean, which affected their perceptions and preferences in relation to caesarean delivery. Conclusion: Most of pregnant women believed that fear of vaginal delivery is a major factor to choose caesarean delivery. Hence, midwives and physicians could help them through improving the quality of prenatal care and giving them positive perception towards vaginal delivery through presenting useful information about the nature of different modes of delivery, and their advantages and disadvantages, as well as the alternative ways to control labor pain. PMID:25949249

Protocol independent transmission method in software defined optical network

Science.gov (United States)

Liu, Yuze; Li, Hui; Hou, Yanfang; Qiu, Yajun; Ji, Yuefeng

2016-10-01

With the development of big data and cloud computing technology, the traditional software-defined network is facing new challenges (e.i., ubiquitous accessibility, higher bandwidth, more flexible management and greater security). Using a proprietary protocol or encoding format is a way to improve information security. However, the flow, which carried by proprietary protocol or code, cannot go through the traditional IP network. In addition, ultra- high-definition video transmission service once again become a hot spot. Traditionally, in the IP network, the Serial Digital Interface (SDI) signal must be compressed. This approach offers additional advantages but also bring some disadvantages such as signal degradation and high latency. To some extent, HD-SDI can also be regard as a proprietary protocol, which need transparent transmission such as optical channel. However, traditional optical networks cannot support flexible traffics . In response to aforementioned challenges for future network, one immediate solution would be to use NFV technology to abstract the network infrastructure and provide an all-optical switching topology graph for the SDN control plane. This paper proposes a new service-based software defined optical network architecture, including an infrastructure layer, a virtualization layer, a service abstract layer and an application layer. We then dwell on the corresponding service providing method in order to implement the protocol-independent transport. Finally, we experimentally evaluate that proposed service providing method can be applied to transmit the HD-SDI signal in the software-defined optical network.

Research on Fault Diagnosis Method Based on Rule Base Neural Network

Directory of Open Access Journals (Sweden)

Zheng Ni

2017-01-01

Full Text Available The relationship between fault phenomenon and fault cause is always nonlinear, which influences the accuracy of fault location. And neural network is effective in dealing with nonlinear problem. In order to improve the efficiency of uncertain fault diagnosis based on neural network, a neural network fault diagnosis method based on rule base is put forward. At first, the structure of BP neural network is built and the learning rule is given. Then, the rule base is built by fuzzy theory. An improved fuzzy neural construction model is designed, in which the calculated methods of node function and membership function are also given. Simulation results confirm the effectiveness of this method.

Network 'small-world-ness': a quantitative method for determining canonical network equivalence.

Directory of Open Access Journals (Sweden)

Mark D Humphries

Full Text Available BACKGROUND: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges. This semi-quantitative definition leads to a categorical distinction ('small/not-small' rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model--the Watts-Strogatz (WS model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. METHODOLOGY/PRINCIPAL FINDINGS: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S>1--an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process. CONCLUSIONS/SIGNIFICANCE: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing.

Momentum integral network method for thermal-hydraulic transient analysis

International Nuclear Information System (INIS)

Van Tuyle, G.J.

1983-01-01

A new momentum integral network method has been developed, and tested in the MINET computer code. The method was developed in order to facilitate the transient analysis of complex fluid flow and heat transfer networks, such as those found in the balance of plant of power generating facilities. The method employed in the MINET code is a major extension of a momentum integral method reported by Meyer. Meyer integrated the momentum equation over several linked nodes, called a segment, and used a segment average pressure, evaluated from the pressures at both ends. Nodal mass and energy conservation determined nodal flows and enthalpies, accounting for fluid compression and thermal expansion

Protocol and networking design issues for local access WDM networks

OpenAIRE

Salvador, M.R.; Heemstra de Groot, S.M.; Niemegeers, I.G.M.M.

1999-01-01

This report gives an overview of some of the protocol and networking design issues that have been addressed in Flamingo, a major ongoing project which investigates the use of WDM optical technology in local access networks. Quality of service delivery and wavelength assignment are focused on in this report. A brief introduction to optical networks and WDM as well as a brief description of Flamingo are also included in this report.

MicroRNA delivery for regenerative medicine.

Science.gov (United States)

Peng, Bo; Chen, Yongming; Leong, Kam W

2015-07-01

MicroRNA (miRNA) directs post-transcriptional regulation of a network of genes by targeting mRNA. Although relatively recent in development, many miRNAs direct differentiation of various stem cells including induced pluripotent stem cells (iPSCs), a major player in regenerative medicine. An effective and safe delivery of miRNA holds the key to translating miRNA technologies. Both viral and nonviral delivery systems have seen success in miRNA delivery, and each approach possesses advantages and disadvantages. A number of studies have demonstrated success in augmenting osteogenesis, improving cardiogenesis, and reducing fibrosis among many other tissue engineering applications. A scaffold-based approach with the possibility of local and sustained delivery of miRNA is particularly attractive since the physical cues provided by the scaffold may synergize with the biochemical cues induced by miRNA therapy. Herein, we first briefly cover the application of miRNA to direct stem cell fate via replacement and inhibition therapies, followed by the discussion of the promising viral and nonviral delivery systems. Next we present the unique advantages of a scaffold-based delivery in achieving lineage-specific differentiation and tissue development. Copyright © 2015 Elsevier B.V. All rights reserved.

Distribution network planning method considering distributed generation for peak cutting

International Nuclear Information System (INIS)

Ouyang Wu; Cheng Haozhong; Zhang Xiubin; Yao Liangzhong

2010-01-01

Conventional distribution planning method based on peak load brings about large investment, high risk and low utilization efficiency. A distribution network planning method considering distributed generation (DG) for peak cutting is proposed in this paper. The new integrated distribution network planning method with DG implementation aims to minimize the sum of feeder investments, DG investments, energy loss cost and the additional cost of DG for peak cutting. Using the solution techniques combining genetic algorithm (GA) with the heuristic approach, the proposed model determines the optimal planning scheme including the feeder network and the siting and sizing of DG. The strategy for the site and size of DG, which is based on the radial structure characteristics of distribution network, reduces the complexity degree of solving the optimization model and eases the computational burden substantially. Furthermore, the operation schedule of DG at the different load level is also provided.

System, apparatus and methods to implement high-speed network analyzers

Science.gov (United States)

Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

2015-11-10

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

A Global Network Alignment Method Using Discrete Particle Swarm Optimization.

Science.gov (United States)

Huang, Jiaxiang; Gong, Maoguo; Ma, Lijia

2016-10-19

Molecular interactions data increase exponentially with the advance of biotechnology. This makes it possible and necessary to comparatively analyse the different data at a network level. Global network alignment is an important network comparison approach to identify conserved subnetworks and get insight into evolutionary relationship across species. Network alignment which is analogous to subgraph isomorphism is known to be an NP-hard problem. In this paper, we introduce a novel heuristic Particle-Swarm-Optimization based Network Aligner (PSONA), which optimizes a weighted global alignment model considering both protein sequence similarity and interaction conservations. The particle statuses and status updating rules are redefined in a discrete form by using permutation. A seed-and-extend strategy is employed to guide the searching for the superior alignment. The proposed initialization method "seeds" matches with high sequence similarity into the alignment, which guarantees the functional coherence of the mapping nodes. A greedy local search method is designed as the "extension" procedure to iteratively optimize the edge conservations. PSONA is compared with several state-of-art methods on ten network pairs combined by five species. The experimental results demonstrate that the proposed aligner can map the proteins with high functional coherence and can be used as a booster to effectively refine the well-studied aligners.

Optimization-based Method for Automated Road Network Extraction

International Nuclear Information System (INIS)

Xiong, D

2001-01-01

Automated road information extraction has significant applicability in transportation. It provides a means for creating, maintaining, and updating transportation network databases that are needed for purposes ranging from traffic management to automated vehicle navigation and guidance. This paper is to review literature on the subject of road extraction and to describe a study of an optimization-based method for automated road network extraction

Application of Looped Network Analysis Method to Core of Prismatic VHTR

International Nuclear Information System (INIS)

Lee, Jeong-Hun; Cho, Hyoung-Kyu; Park, Goon-Cherl

2016-01-01

Most of reactor coolant flows through the coolant channel within the fuel block, but some portion of the reactor coolant bypasses to the interstitial gaps. The vertical gap and horizontal gap are called bypass gap and cross gap, respectively as shown in Fig. 1. CFD simulation for the full core of VHTR might be possible but it requires vast computational cost and time. Moreover, it is hard to cover whole cases corresponding to the various bypass gap distribution in the whole VHTR core. In order to solve this problem, in this study, the flow network analysis code, FastNet (Flow Analysis for Steady-state Network), was developed using the Looped Network Analysis Method. The applied method was validated by comparing with SNU VHTR multi-block experiment. A 3-demensional network modeling was conducted representing flow paths as flow resistances. Flow network analysis code, FastNet, was developed to evaluate the core bypass flow distribution by using looped network analysis method. Complex flow network could be solved simply by converting the non-linear momentum equation to the linearized equation. The FastNet code predicted the flow distribution of the SNU multi-block experiment accurately

Optical broadband in-home networks for converged service delivery

NARCIS (Netherlands)

Shi, Y.

2013-01-01

Broadband access networks, and in particular fibre-to-the-home (FTTH) networks, are offering abundantly available bandwidth in the local loop with high quality of services. Under such broadband connectivity conditions, in-home networks should not represent the bottleneck for high capacity service

Development of strategies to reduce cesarean delivery rates in iran 2012-2014: A mixed methods study

Directory of Open Access Journals (Sweden)

Razieh Lotfi

2014-01-01

Full Text Available Background: With the change in population policy from birth control toward encouraging birth and population growth in Iran, repeated cesarean deliveries as a main reason of cesarean section are associated with more potential adverse consequences. The aim of this research was to explore effective strategies to reduce cesarean delivery rates in Iran. Methods: A mixed methodological study was designed and implemented. First, using a qualitative approach, concepts and influencing factors of increased cesarean delivery were explored. Based on the findings of this phase of the study, a questionnaire including the proposed strategies to reduce cesarean delivery was developed. Then in a quantitative phase, the questionnaire was assessed by key informants from across the country and evaluated to obtain more effective strategies to reduce cesarean delivery. Ten participants in the qualitative study included policy makers from the Ministry of Health, obstetricians, midwives and anthropologists. In the next step, 141 participants from private and public hospitals, insurance experts, Academic Associations of Midwifery, and policy makers in Maternity Health Affairs of Ministry of Health were invited to assess and provide feedback on the strategies that work to reduce cesarean deliveries. Results: Qualitative data analysis showed four concept related to increased cesarean delivery rates including; "standardization", "education", "amending regulations", and "performance supervision". Effective strategies extracted from qualitative data were rated by participants then, using ACCEPT derived from A as attainability, C as costing, C as complication, E as effectiveness, P as popularity, and T as timing table 19 strategies were detected as priorities. Conclusions: Although developing effective strategies to reduce cesarean delivery rates is complex process because of the multi-factorial nature of increased cesarean deliveries, in this study we have achieved

Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks

KAUST Repository

Shnaiwer, Yousef N.; Sorour, Sameh; Aboutorab, Neda; Sadeghi, Parastoo; Al-Naffouri, Tareq Y.

2015-01-01

Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrary non-fragmented placement of such files, a strict no-latency constraint, and clients' prior knowledge, new file download requests could be efficiently handled by both the FCs and the macrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBS involvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes the number of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among the FC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

Network-Coded Content Delivery in Femtocaching-Assisted Cellular Networks

KAUST Repository

Shnaiwer, Yousef N.

2015-12-06

Next-generation cellular networks are expected to be assisted by femtocaches (FCs), which collectively store the most popular files for the clients. Given any arbitrary non-fragmented placement of such files, a strict no-latency constraint, and clients\\' prior knowledge, new file download requests could be efficiently handled by both the FCs and the macrocell base station (MBS) using opportunistic network coding (ONC). In this paper, we aim to find the best allocation of coded file downloads to the FCs so as to minimize the MBS involvement in this download process. We first formulate this optimization problem over an ONC graph, and show that it is NP-hard. We then propose a greedy approach that maximizes the number of files downloaded by the FCs, with the goal to reduce the download share of the MBS. This allocation is performed using a dual conflict ONC graph to avoid conflicts among the FC downloads. Simulations show that our proposed scheme almost achieves the optimal performance and significantly saves on the MBS bandwidth.

Assessment of network inference methods: how to cope with an underdetermined problem.

Directory of Open Access Journals (Sweden)

Caroline Siegenthaler

Full Text Available The inference of biological networks is an active research area in the field of systems biology. The number of network inference algorithms has grown tremendously in the last decade, underlining the importance of a fair assessment and comparison among these methods. Current assessments of the performance of an inference method typically involve the application of the algorithm to benchmark datasets and the comparison of the network predictions against the gold standard or reference networks. While the network inference problem is often deemed underdetermined, implying that the inference problem does not have a (unique solution, the consequences of such an attribute have not been rigorously taken into consideration. Here, we propose a new procedure for assessing the performance of gene regulatory network (GRN inference methods. The procedure takes into account the underdetermined nature of the inference problem, in which gene regulatory interactions that are inferable or non-inferable are determined based on causal inference. The assessment relies on a new definition of the confusion matrix, which excludes errors associated with non-inferable gene regulations. For demonstration purposes, the proposed assessment procedure is applied to the DREAM 4 In Silico Network Challenge. The results show a marked change in the ranking of participating methods when taking network inferability into account.

Obstetric care and method of delivery in Mexico: results from the 2012 National Health and Nutrition Survey.

Directory of Open Access Journals (Sweden)

Ileana Heredia-Pi

Full Text Available OBJECTIVE: To identify the current clinical, socio-demographic and obstetric factors associated with the various types of delivery strategies in Mexico. MATERIALS AND METHODS: This is a cross-sectional study based on the 2012 National Health and Nutrition Survey (ENSANUT of 6,736 women aged 12 to 49 years. Delivery types discussed in this paper include vaginal delivery, emergency cesarean section and planned cesarean section. Using bivariate analyses, sub-population group differences were identified. Logistic regression models were applied, including both binary and multinomial outcome variables from the survey. The logistic regression results identify those covariates associated with the type of delivery. RESULTS: 53.1% of institutional births in the period 2006 through 2012 were vaginal deliveries, 46.9% were either a planned or emergency cesarean sections. The highest rates of this procedure were among women who reported a complication during delivery (OR: 4.21; 95%CI: 3.66-4.84, between the ages of 35 and 49 at the time of their last child birth (OR: 2.54; 95%CI: 2.02-3.20 and women receiving care through private healthcare providers during delivery (OR: 2.36; 95%CI: 1.84-3.03. CONCLUSIONS: The existence of different socio-demographic and obstetric profiles among women who receive care for vaginal or cesarean delivery, are supported by the findings of the present study. The frequency of vaginal delivery is higher in indigenous women, when the care provider is public and, in women with two or more children at time of the most recent child birth. Planned cesarean deliveries are positively associated with years of schooling, a higher socioeconomic level, and higher age. The occurrence of emergency cesarean sections is elevated in women with a diagnosis of a health issue during pregnancy or delivery, and it is reduced in highly marginalized settings.

Improved routing strategies for data traffic in scale-free networks

International Nuclear Information System (INIS)

Wu, Zhi-Xi; Peng, Gang; Wong, Wing-Ming; Yeung, Kai-Hau

2008-01-01

We study the information packet routing process in scale-free networks by mimicking Internet traffic delivery. We incorporate both the global shortest paths information and local degree information of the network in the dynamic process, via two tunable parameters, α and β, to guide the packet routing. We measure the performance of the routing method by both the average transit times of packets and the critical packet generation rate (above which packet aggregation occurs in the network). We found that the routing strategies which integrate ingredients of both global and local topological information of the underlying networks perform much better than the traditional shortest path routing protocol taking into account the global topological information only. Moreover, by doing comparative studies with some related works, we found that the performance of our proposed method shows universal efficiency characteristic against the amount of traffic

Comparing two instructional methods of role playing and lecture on primigravida females, decision about type of delivery.

Science.gov (United States)

Abedian, Zahra; Navaee, Maryam; Sani, Hossein Jafari; Ebrahimzadeh, Saeed

2017-01-01

Each mother has the legal right to decide about her delivery, but this decision should be made based on scientific knowledge. Instructions during pregnancy help to choose the proper type of delivery. This study conducted aimed to compare two instructional methods of role playing and lecture on primigravida decision about type of delivery. In this single-blind clinical trial 67 primigravida, 34-36 week were selected using multi-stage sampling and assigned into two groups randomly. Decision-making (before, 2-week after, and at admission in maternity department) was tested by a questionnaire. In role-playing group, advantages and disadvantages of two type delivery were presented by role-playing in 90-min by three scenarios. In lecture group, it was also presented in a 90-min lecture. Data were analyzed by mean difference test, Fisher test, independent and paired t -test. Two groups showed a significant difference in terms of decision at admission to maternity department ( P = 0.000). 75% of lecture group and 100% of role-playing group selected normal delivery. Postintervention knowledge score in lecture group was 18 ± 5.3 and in role-playing group 17.1 ± 4.0. Percent of change in knowledge scores in two groups was significant ( P = 0.001). Participants' attitude, before and after the intervention, in both groups was significant ( P 0.05). In this research, lecture was more effective in raising knowledge level, and role playing was more effective in raising decision to vaginal delivery and reducing elective caesarean section. It is therefore suggested to use both teaching methods altogether for pregnant women to decrease the rate of unnecessary cesarean.

ATM: The Key To Harnessing the Power of Networked Multimedia.

Science.gov (United States)

Gross, Rod

1996-01-01

ATM (Asynchronous Transfer Mode) network technology handles the real-time continuous traffic flow necessary to support desktop multimedia applications. Describes network applications already used: desktop video collaboration, distance learning, and broadcasting video delivery. Examines the architecture of ATM technology, video delivery and sound…

Soil chemical sensor and precision agricultural chemical delivery system and method

Science.gov (United States)

Colburn, Jr., John W.

1991-01-01

A real time soil chemical sensor and precision agricultural chemical delivery system includes a plurality of ground-engaging tools in association with individual soil sensors which measure soil chemical levels. The system includes the addition of a solvent which rapidly saturates the soil/tool interface to form a conductive solution of chemicals leached from the soil. A multivalent electrode, positioned within a multivalent frame of the ground-engaging tool, applies a voltage or impresses a current between the electrode and the tool frame. A real-time soil chemical sensor and controller senses the electrochemical reaction resulting from the application of the voltage or current to the leachate, measures it by resistivity methods, and compares it against pre-set resistivity levels for substances leached by the solvent. Still greater precision is obtained by calibrating for the secondary current impressed through solvent-less soil. The appropriate concentration is then found and the servo-controlled delivery system applies the appropriate amount of fertilizer or agricultural chemicals substantially in the location from which the soil measurement was taken.

Engaging children and parents in service design and delivery.

Science.gov (United States)

Bedford Russell, A R; Passant, M; Kitt, H

2014-12-01

The involvement of all user groups, including children, young people (CYP) and their parents, encourages people to take responsibility for healthier lifestyle behaviours, improves treatment compliance and leads to more appropriate use of healthcare resources. Initiatives to engage CYP in the UK are gathering momentum, but significant improvements are still needed. There is a national drive from the department of health (DH) and NHS England, strategic clinical networks, operational delivery networks (including newborn networks), charities, parent groups and a number of other bodies to embed CYP involvement in service design and delivery. User engagement and patient choice, is underpinned by the NHS outcomes framework, and a myriad of other DH and NHS England policies and practice frameworks. It is now everybody's business. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Crosslinked ionic polysaccharides for stimuli-sensitive drug delivery.

Science.gov (United States)

Alvarez-Lorenzo, Carmen; Blanco-Fernandez, Barbara; Puga, Ana M; Concheiro, Angel

2013-08-01

Polysaccharides are gaining increasing attention as components of stimuli-responsive drug delivery systems, particularly since they can be obtained in a well characterized and reproducible way from the natural sources. Ionic polysaccharides can be readily crosslinked to render hydrogel networks sensitive to a variety of internal and external variables, and thus suitable for switching drug release on-off through diverse mechanisms. Hybrids, composites and grafted polymers can reinforce the responsiveness and widen the range of stimuli to which polysaccharide-based systems can respond. This review analyzes the state of the art of crosslinked ionic polysaccharides as components of delivery systems that can regulate drug release as a function of changes in pH, ion nature and concentration, electric and magnetic field intensity, light wavelength, temperature, redox potential, and certain molecules (enzymes, illness markers, and so on). Examples of specific applications are provided. The information compiled demonstrates that crosslinked networks of ionic polysaccharides are suitable building blocks for developing advanced externally activated and feed-back modulated drug delivery systems. Copyright © 2013 Elsevier B.V. All rights reserved.

Input data preprocessing method for exchange rate forecasting via neural network

Directory of Open Access Journals (Sweden)

Antić Dragan S.

2014-01-01

Full Text Available The aim of this paper is to present a method for neural network input parameters selection and preprocessing. The purpose of this network is to forecast foreign exchange rates using artificial intelligence. Two data sets are formed for two different economic systems. Each system is represented by six categories with 70 economic parameters which are used in the analysis. Reduction of these parameters within each category was performed by using the principal component analysis method. Component interdependencies are established and relations between them are formed. Newly formed relations were used to create input vectors of a neural network. The multilayer feed forward neural network is formed and trained using batch training. Finally, simulation results are presented and it is concluded that input data preparation method is an effective way for preprocessing neural network data. [Projekat Ministarstva nauke Republike Srbije, br.TR 35005, br. III 43007 i br. III 44006

Athena: Towards Decision-Centric Anticipatory Sensor Information Delivery

Directory of Open Access Journals (Sweden)

Jongdeog Lee

2018-01-01

Full Text Available The paper introduces a new direction in quality-of-service-aware networked sensing that designs communication protocols and scheduling policies for data delivery that are optimized specifically for decision needs. The work complements present decision monitoring and support tools and falls in the larger framework of decision-driven resource management. A hallmark of the new protocols is that they are aware of the inference structure used to arrive at decisions (from logical predicates, as well as the data (and data quality that need to be furnished to successfully evaluate the unknowns on which these decisions are based. Such protocols can therefore anticipate and deliver precisely the right data, at the right level of quality, from the right sources, at the right time, to enable valid and timely decisions at minimum cost to the underlying network. This paper presents the decision model used and the protocol design philosophy, reviews the key recent results and describes a novel system, called Athena, that is the first to embody the aforementioned data delivery paradigm. Evaluation results are presented that compare the performance of decision-centric anticipatory information delivery to several baselines, demonstrating its various advantages in terms of decision timeliness, validity and network resources used. The paper concludes with a discussion of remaining future challenges in this emerging area.

AN IMPROVEMENT ON GEOMETRY-BASED METHODS FOR GENERATION OF NETWORK PATHS FROM POINTS

Directory of Open Access Journals (Sweden)

Z. Akbari

2014-10-01

Full Text Available Determining network path is important for different purposes such as determination of road traffic, the average speed of vehicles, and other network analysis. One of the required input data is information about network path. Nevertheless, the data collected by the positioning systems often lead to the discrete points. Conversion of these points to the network path have become one of the challenges which different researchers, presents many ways for solving it. This study aims at investigating geometry-based methods to estimate the network paths from the obtained points and improve an existing point to curve method. To this end, some geometry-based methods have been studied and an improved method has been proposed by applying conditions on the best method after describing and illustrating weaknesses of them.

Reliable Download Delivery in a Terrestrial DAB Network

NARCIS (Netherlands)

Schiphorst, Roelof; Shao, X.; Slump, Cornelis H.

2008-01-01

Reliable file transfer is important in broadcast networks. In this paper, we have investigated if it is useful to extend the DAB standard with Fountain codes. To evaluate this, results from measurements in a live Single Frequency Network (SFN) were used. Our results show that the existing error

Study on Dissemination Patterns in Location-Aware Gossiping Networks

Science.gov (United States)

Kami, Nobuharu; Baba, Teruyuki; Yoshikawa, Takashi; Morikawa, Hiroyuki

We study the properties of information dissemination over location-aware gossiping networks leveraging location-based real-time communication applications. Gossiping is a promising method for quickly disseminating messages in a large-scale system, but in its application to information dissemination for location-aware applications, it is important to consider the network topology and patterns of spatial dissemination over the network in order to achieve effective delivery of messages to potentially interested users. To this end, we propose a continuous-space network model extended from Kleinberg's small-world model applicable to actual location-based applications. Analytical and simulation-based study shows that the proposed network achieves high dissemination efficiency resulting from geographically neutral dissemination patterns as well as selective dissemination to proximate users. We have designed a highly scalable location management method capable of promptly updating the network topology in response to node movement and have implemented a distributed simulator to perform dynamic target pursuit experiments as one example of applications that are the most sensitive to message forwarding delay. The experimental results show that the proposed network surpasses other types of networks in pursuit efficiency and achieves the desirable dissemination patterns.

Coupling surfactants with permanganate for DNAPL removal : coinjection or sequential application as delivery methods

Energy Technology Data Exchange (ETDEWEB)

Dugan, P.J. [Carus Corp., Peru, IL (United States); Siegrist, R.L. [Colorado School of Mines, Golden, CO (United States); Crimi, M.L. [Clarkson Univ., Potsdam, NY (United States)

2010-07-01

This PowerPoint presentation described a study conducted to test the effectiveness of surfactant-enhanced permanganate for the remediation of dense nonaqueous phase liquids (DNAPL). When DNAPL enters the environment, it can pollute millions of gallons of ground water and create huge dissolved plumes that act as long-term sources of contamination. Surfactants were used to enhance the solubilization and mobilization of DNAPL during the remediation process. In situ chemical oxidation (ISCO) was then used to deliver oxidants into the sub-surface to destroy organic contaminants in the soil and ground water. Experimental 2-D flow-through cell studies of 72 surfactants were conducted with the permanganate to evaluate delivery methods and determine compatible co-solvents for the surfactant process. Delivery methods included co-injection and sequential application. Four compatible surfactants were found to be compatible with the permanganate. A 90 percent DNAPL remediation rate was achieved using relatively low surfactant and oxidant concentrations. tabs., figs.

A hierarchical network modeling method for railway tunnels safety assessment

Science.gov (United States)

Zhou, Jin; Xu, Weixiang; Guo, Xin; Liu, Xumin

2017-02-01

Using network theory to model risk-related knowledge on accidents is regarded as potential very helpful in risk management. A large amount of defects detection data for railway tunnels is collected in autumn every year in China. It is extremely important to discover the regularities knowledge in database. In this paper, based on network theories and by using data mining techniques, a new method is proposed for mining risk-related regularities to support risk management in railway tunnel projects. A hierarchical network (HN) model which takes into account the tunnel structures, tunnel defects, potential failures and accidents is established. An improved Apriori algorithm is designed to rapidly and effectively mine correlations between tunnel structures and tunnel defects. Then an algorithm is presented in order to mine the risk-related regularities table (RRT) from the frequent patterns. At last, a safety assessment method is proposed by consideration of actual defects and possible risks of defects gained from the RRT. This method cannot only generate the quantitative risk results but also reveal the key defects and critical risks of defects. This paper is further development on accident causation network modeling methods which can provide guidance for specific maintenance measure.

An efficient parallel stochastic simulation method for analysis of nonviral gene delivery systems

KAUST Repository

Kuwahara, Hiroyuki

2011-01-01

Gene therapy has a great potential to become an effective treatment for a wide variety of diseases. One of the main challenges to make gene therapy practical in clinical settings is the development of efficient and safe mechanisms to deliver foreign DNA molecules into the nucleus of target cells. Several computational and experimental studies have shown that the design process of synthetic gene transfer vectors can be greatly enhanced by computational modeling and simulation. This paper proposes a novel, effective parallelization of the stochastic simulation algorithm (SSA) for pharmacokinetic models that characterize the rate-limiting, multi-step processes of intracellular gene delivery. While efficient parallelizations of the SSA are still an open problem in a general setting, the proposed parallel simulation method is able to substantially accelerate the next reaction selection scheme and the reaction update scheme in the SSA by exploiting and decomposing the structures of stochastic gene delivery models. This, thus, makes computationally intensive analysis such as parameter optimizations and gene dosage control for specific cell types, gene vectors, and transgene expression stability substantially more practical than that could otherwise be with the standard SSA. Here, we translated the nonviral gene delivery model based on mass-action kinetics by Varga et al. [Molecular Therapy, 4(5), 2001] into a more realistic model that captures intracellular fluctuations based on stochastic chemical kinetics, and as a case study we applied our parallel simulation to this stochastic model. Our results show that our simulation method is able to increase the efficiency of statistical analysis by at least 50% in various settings. © 2011 ACM.

Methodical approach to training of IT-professionals based on networking

Directory of Open Access Journals (Sweden)

Vyacheslav V. Zolotarev

2017-12-01

Full Text Available Increasing requirements to the content and form of higher education in conditions of digital economy set new tasks for professors: formation of applied competences, the involvement of students in project activities, provision of students’ online support, their individual and project work. The growing load on university professors complicates satisfaction of these requirements. The development of the professors’ network interaction makes it possible to redistribute the load for disciplines methodological provision. The article reveals possibilities of professors’ network interaction by using innovative teaching methods including gaming forms and online courses. The research scientific novelty is to implement the professors’ network interaction and experimental application of innovative teaching methods. Network interaction was carried out through the educational process of students’ preparation in following areas: information security, applied information technology, business informatics.

Normal Range of Head-to-body Delivery Interval by Two-step Delivery

Directory of Open Access Journals (Sweden)

Hong-Yu Zhang

2016-01-01

Conclusions: The average time of head-to-body delivery interval was longer than 60 s by two-step delivery. Majority shoulders were delivered at the first contraction. Majority shoulders emerged from perineum rather from under pubic arch. The routine one-step method of shoulder delivery where the downward force applied is not necessary and is not the right direction. Baby's breath, making faces, sucking, bubble from noses and mouth, and the light blue color of the faces, all those signs during shoulder delivery indicated a normal live birth.

A new metric method-improved structural holes researches on software networks

Science.gov (United States)

Li, Bo; Zhao, Hai; Cai, Wei; Li, Dazhou; Li, Hui

2013-03-01

The scale software systems quickly increase with the rapid development of software technologies. Hence, how to understand, measure, manage and control software structure is a great challenge for software engineering. there are also many researches on software networks metrics: C&K, MOOD, McCabe and etc, the aim of this paper is to propose a new and better method to metric software networks. The metric method structural holes are firstly introduced to in this paper, which can not directly be applied as a result of modular characteristics on software network. Hence, structural holes is redefined in this paper and improved, calculation process and results are described in detail. The results shows that the new method can better reflect bridge role of vertexes on software network and there is a significant correlation between degree and improved structural holes. At last, a hydropower simulation system is taken as an example to show validity of the new metric method.

Fault diagnosis method for nuclear power plants based on neural networks and voting fusion

International Nuclear Information System (INIS)

Zhou Gang; Ge Shengqi; Yang Li

2010-01-01

A new fault diagnosis method based on multiple neural networks (ANNs) and voting fusion for nuclear power plants (NPPs) was proposed in view of the shortcoming of single neural network fault diagnosis method. In this method, multiple neural networks that the types of neural networks were different were trained for the fault diagnosis of NPP. The operation parameters of NPP, which have important affect on the safety of NPP, were selected as the input variable of neural networks. The output of neural networks is fault patterns of NPP. The last results of diagnosis for NPP were obtained by fusing the diagnosing results of different neural networks by voting fusion. The typical operation patterns of NPP were diagnosed to demonstrate the effect of the proposed method. The results show that employing the proposed diagnosing method can improve the precision and reliability of fault diagnosis results of NPPs. (authors)

Non-Viral Transfection Methods Optimized for Gene Delivery to a Lung Cancer Cell Line

OpenAIRE

Salimzadeh, Loghman; Jaberipour, Mansooreh; Hosseini, Ahmad; Ghaderi, Abbas

2013-01-01

Background Mehr-80 is a newly established adherent human large cell lung cancer cell line that has not been transfected until now. This study aims to define the optimal transfection conditions and effects of some critical elements for enhancing gene delivery to this cell line by utilizing different non-viral transfection Procedures. Methods In the current study, calcium phosphate (CaP), DEAE-dextran, superfect, electroporation and lipofection transfection methods were used to optimize deliver...

Training Delivery Methods as Source of Dynamic Capabilities: The Case of Sports' Organisations

Science.gov (United States)

Arraya, Marco António Mexia; Porfírio, Jose António

2017-01-01

Purpose: Training as an important source of dynamic capabilities (DC) is important to the performance of sports' organisations (SO) both to athletes and to non-athletic staff. There are a variety of training delivery methods (TDMs). The purpose of this study is to determine from a set of six TDMs which one is considered to be the most suitable to…

Improved overall delivery documentation following implementation of a standardized shoulder dystocia delivery form

Science.gov (United States)

Moragianni, Vasiliki A.; Hacker, Michele R.; Craparo, Frank J.

2013-01-01

Objective Our objective was to evaluate whether using a standardized shoulder dystocia delivery form improved documentation. A standardized delivery form was added to our institution’s obstetrical record in August 2003. Methods A retrospective cohort study was conducted comparing 100 vaginal deliveries complicated by shoulder dystocia before, and 81 after implementation of the standardized delivery form. The two groups were compared in terms of obstetric characteristics, neonatal outcomes and documentation components. Results Charts that included the standardized delivery form were more likely to contain documentation of estimated fetal weight (82.7% vs. 39.0% without the form, Pdystocia, and second stage duration. Conclusions Inclusion of a standardized form in the delivery record improves the rate of documentation of both shoulder dystocia-specific and general delivery components. PMID:22017330

Diagrammatic perturbation methods in networks and sports ranking combinatorics

International Nuclear Information System (INIS)

Park, Juyong

2010-01-01

Analytic and computational tools developed in statistical physics are being increasingly applied to the study of complex networks. Here we present recent developments in the diagrammatic perturbation methods for the exponential random graph models, and apply them to the combinatoric problem of determining the ranking of nodes in directed networks that represent pairwise competitions

A method for identifying hierarchical sub-networks / modules and weighting network links based on their similarity in sub-network / module affiliation

Directory of Open Access Journals (Sweden)

WenJun Zhang

2016-06-01

Full Text Available Some networks, including biological networks, consist of hierarchical sub-networks / modules. Based on my previous study, in present study a method for both identifying hierarchical sub-networks / modules and weighting network links is proposed. It is based on the cluster analysis in which between-node similarity in sets of adjacency nodes is used. Two matrices, linkWeightMat and linkClusterIDs, are achieved by using the algorithm. Two links with both the same weight in linkWeightMat and the same cluster ID in linkClusterIDs belong to the same sub-network / module. Two links with the same weight in linkWeightMat but different cluster IDs in linkClusterIDs belong to two sub-networks / modules at the same hirarchical level. However, a link with an unique cluster ID in linkClusterIDs does not belong to any sub-networks / modules. A sub-network / module of the greater weight is the more connected sub-network / modules. Matlab codes of the algorithm are presented.

METHODS OF POLYMODAL INFORMATION TRANSMISSION

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O. O. Basov

2015-03-01

Full Text Available The research results upon the application of the existing information transmission methods in polymodal info communication systems are presented herein. The analysis of the existing commutation ways and multiplexing schemes has revealed that modern means of telecommunication are capable of providing polymodal information delivery with the required quality to the customer correspondent terminal. Under these conditions substantial capacity resource consumption in the data transmission networks with a simultaneous static time multiplexing is required, however, it is easier to achieve the modality synchronization within that kind of an infrastructure. The data networks with a static time multiplexing demand employing more sophisticated supporting algorithms of the guaranteed data blocks delivery quality. However, due to the stochastic data blocks delays modality synchronizing during the off-line processing is more difficult to provide. Nowadays there are objective preconditions for a data networking realization which is invariable to the applied transmission technology. This capability is defined by a wide (person-to-person application of the optical technologies in the transport infrastructure of the polymodal info communication systems. In case of the availability of the customer terminal and networking functioning matching mode it becomes possible to organize channels in the latter which can adaptively select the most effective networking technology according to the current volume allocation and modality types in the messages.

Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator

International Nuclear Information System (INIS)

Zhou Gang; Yang Li

2009-01-01

A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)

A comparative analysis on computational methods for fitting an ERGM to biological network data

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Sudipta Saha

2015-03-01

Full Text Available Exponential random graph models (ERGM based on graph theory are useful in studying global biological network structure using its local properties. However, computational methods for fitting such models are sensitive to the type, structure and the number of the local features of a network under study. In this paper, we compared computational methods for fitting an ERGM with local features of different types and structures. Two commonly used methods, such as the Markov Chain Monte Carlo Maximum Likelihood Estimation and the Maximum Pseudo Likelihood Estimation are considered for estimating the coefficients of network attributes. We compared the estimates of observed network to our random simulated network using both methods under ERGM. The motivation was to ascertain the extent to which an observed network would deviate from a randomly simulated network if the physical numbers of attributes were approximately same. Cut-off points of some common attributes of interest for different order of nodes were determined through simulations. We implemented our method to a known regulatory network database of Escherichia coli (E. coli.

Inference of directed climate networks: role of instability of causality estimation methods

Science.gov (United States)

Hlinka, Jaroslav; Hartman, David; Vejmelka, Martin; Paluš, Milan

2013-04-01

Climate data are increasingly analyzed by complex network analysis methods, including graph-theoretical approaches [1]. For such analysis, links between localized nodes of climate network are typically quantified by some statistical measures of dependence (connectivity) between measured variables of interest. To obtain information on the directionality of the interactions in the networks, a wide range of methods exists. These can be broadly divided into linear and nonlinear methods, with some of the latter having the theoretical advantage of being model-free, and principally a generalization of the former [2]. However, as a trade-off, this generality comes together with lower accuracy - in particular if the system was close to linear. In an overall stationary system, this may potentially lead to higher variability in the nonlinear network estimates. Therefore, with the same control of false alarms, this may lead to lower sensitivity for detection of real changes in the network structure. These problems are discussed on the example of daily SAT and SLP data from the NCEP/NCAR reanalysis dataset. We first reduce the dimensionality of data using PCA with VARIMAX rotation to detect several dozens of components that together explain most of the data variability. We further construct directed climate networks applying a selection of most widely used methods - variants of linear Granger causality and conditional mutual information. Finally, we assess the stability of the detected directed climate networks by computing them in sliding time windows. To understand the origin of the observed instabilities and their range, we also apply the same procedure to two types of surrogate data: either with non-stationarity in network structure removed, or imposed in a controlled way. In general, the linear methods show stable results in terms of overall similarity of directed climate networks inferred. For instance, for different decades of SAT data, the Spearman correlation of edge

Comparative study of discretization methods of microarray data for inferring transcriptional regulatory networks

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Ji Wei

2010-10-01

Full Text Available Abstract Background Microarray data discretization is a basic preprocess for many algorithms of gene regulatory network inference. Some common discretization methods in informatics are used to discretize microarray data. Selection of the discretization method is often arbitrary and no systematic comparison of different discretization has been conducted, in the context of gene regulatory network inference from time series gene expression data. Results In this study, we propose a new discretization method "bikmeans", and compare its performance with four other widely-used discretization methods using different datasets, modeling algorithms and number of intervals. Sensitivities, specificities and total accuracies were calculated and statistical analysis was carried out. Bikmeans method always gave high total accuracies. Conclusions Our results indicate that proper discretization methods can consistently improve gene regulatory network inference independent of network modeling algorithms and datasets. Our new method, bikmeans, resulted in significant better total accuracies than other methods.

Evaluation of gene association methods for coexpression network construction and biological knowledge discovery.

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Sapna Kumari

Full Text Available BACKGROUND: Constructing coexpression networks and performing network analysis using large-scale gene expression data sets is an effective way to uncover new biological knowledge; however, the methods used for gene association in constructing these coexpression networks have not been thoroughly evaluated. Since different methods lead to structurally different coexpression networks and provide different information, selecting the optimal gene association method is critical. METHODS AND RESULTS: In this study, we compared eight gene association methods - Spearman rank correlation, Weighted Rank Correlation, Kendall, Hoeffding's D measure, Theil-Sen, Rank Theil-Sen, Distance Covariance, and Pearson - and focused on their true knowledge discovery rates in associating pathway genes and construction coordination networks of regulatory genes. We also examined the behaviors of different methods to microarray data with different properties, and whether the biological processes affect the efficiency of different methods. CONCLUSIONS: We found that the Spearman, Hoeffding and Kendall methods are effective in identifying coexpressed pathway genes, whereas the Theil-sen, Rank Theil-Sen, Spearman, and Weighted Rank methods perform well in identifying coordinated transcription factors that control the same biological processes and traits. Surprisingly, the widely used Pearson method is generally less efficient, and so is the Distance Covariance method that can find gene pairs of multiple relationships. Some analyses we did clearly show Pearson and Distance Covariance methods have distinct behaviors as compared to all other six methods. The efficiencies of different methods vary with the data properties to some degree and are largely contingent upon the biological processes, which necessitates the pre-analysis to identify the best performing method for gene association and coexpression network construction.

Factors associated with institutional delivery service utilization in Ethiopia

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Kebede A

2016-09-01

Full Text Available Alemi Kebede,1 Kalkidan Hassen,2 Aderajew Nigussie Teklehaymanot1 1Department of Population and Family Health, 2College of Health Sciences, Jimma University, Ethiopia Background: Most obstetric complications occur unpredictably during the time of delivery, but they can be prevented with proper medical care in the health facilities. Despite the Ethiopian government’s efforts to expand health service facilities and promote health institution-based delivery service in the country, an estimated 85% of births still take place at home.Objective: The review was conducted with the aim of generating the best evidence on the determinants of institutional delivery service utilization in Ethiopia.Methods: The reviewed studies were accessed through electronic web-based search strategy from PubMed, HINARI, Mendeley reference manager, Cochrane Library for Systematic Reviews, and Google Scholar. Review Manager V5.3 software was used for meta-analysis. Mantel–Haenszel odds ratios (ORs and their 95% confidence intervals (CIs were calculated. Heterogeneity of the study was assessed using I2 test.Results: People living in urban areas (OR =13.16, CI =1.24, 3.68, with primary and above educational level of the mother and husband (OR =4.95, CI =2.3, 4. 8, and OR =4.43, CI =1.14, 3.36, respectively, who encountered problems during pregnancy (OR =2.83, CI =4.54, 7.39, and living at a distance <5 km from nearby health facility (OR =2.6, CI =3.33, 6.57 showed significant association with institutional delivery service utilization. Women’s autonomy was not significantly associated with institutional delivery service utilization.Conclusion and recommendation: Distance to health facility and problems during pregnancy were factors positively and significantly associated with institutional delivery service utilization. Promoting couples education beyond primary education regarding the danger signs of pregnancy and benefits of institutional delivery through available

A MODIFICATION OF THE METHOD CALLED “SUM” WITH THE TIME CONSTRAINTS OF DELIVERY OF GOODS

Directory of Open Access Journals (Sweden)

Sergey Nikolayevich Prosov

2017-05-01

Full Text Available The heuristic procedure considered the shift-daily planning of delivery routes method “amounts”. We present the solution of the transportation problem or the routing problem in efficiency optimization of transportation.

Optical methods for creating delivery systems of chemical compounds to plant roots

Science.gov (United States)

Kuznetsov, Pavel E.; Rogacheva, Svetlana M.; Arefeva, Oksana A.; Minin, Dmitryi V.; Tolmachev, Sergey A.; Kupadze, Machammad S.

2004-08-01

Spectrophotometric and fluorescence methods have been used for creation and investigation of various systems of target delivery of chemical compounds to roots of plants. The possibility of using liposomes, incrusted by polysaccharides of the external surface of nitrogen-fixing rizospheric bacteria Azospirillum brasilense SP 245, and nanoparticles incrusted by polysaccharides of wheat roots, as the named systems has been shown. The important role of polysaccharide-polysaccharide interaction in the adsorption processes of bacteria on wheat roots has been demonstrated.

A fully electronic intensity-modulated radiation therapy quality assurance (IMRT QA) process implemented in a network comprised of independent treatment planning, record and verify, and delivery systems

International Nuclear Information System (INIS)

Bailey, Daniel W; Kumaraswamy, Lalith; Podgorsak, Matthew B

2010-01-01

The purpose of this study is to implement an electronic method to perform and analyze intensity-modulated radiation therapy quality assurance (IMRT QA) using an aSi megavoltage electronic portal imaging device in a network comprised of independent treatment planning, record and verify (R&V), and delivery systems. A verification plan was generated in the treatment planning system using the actual treatment plan of a patient. After exporting the treatment fields to the R&V system, the fields were delivered in QA mode with the aSi imager deployed. The resulting dosimetric images are automatically stored in a DICOM-RT format in the delivery system treatment console computer. The relative dose density images are subsequently pushed to the R&V system. The absolute dose images are then transferred electronically from the treatment console computer to the treatment planning system and imported into the verification plan in the dosimetry work space for further analysis. Screen shots of the gamma evaluation and isodose comparison are imported into the R&V system as an electronic file (e.g. PDF) to be reviewed prior to initiation of patient treatment. A relative dose image predicted by the treatment planning system can also be sent to the R&V system to be compared with the relative dose density image measured with the aSi imager. Our department does not have integrated planning, R&V, and delivery systems. In spite of this, we are able to fully implement a paperless and filmless IMRT QA process, allowing subsequent analysis and approval to be more efficient, while the QA document is directly attached to its specific patient chart in the R&V system in electronic form. The calculated and measured relative dose images can be compared electronically within the R&V system to analyze the density differences and ensure proper dose delivery to patients. In the absence of an integrated planning, verifying, and delivery system, we have shown that it is nevertheless possible to develop a

Applying self-organizing map and modified radial based neural network for clustering and routing optimal path in wireless network

Science.gov (United States)

Hoomod, Haider K.; Kareem Jebur, Tuka

2018-05-01

Mobile ad hoc networks (MANETs) play a critical role in today’s wireless ad hoc network research and consist of active nodes that can be in motion freely. Because it consider very important problem in this network, we suggested proposed method based on modified radial basis function networks RBFN and Self-Organizing Map SOM. These networks can be improved by the use of clusters because of huge congestion in the whole network. In such a system, the performance of MANET is improved by splitting the whole network into various clusters using SOM. The performance of clustering is improved by the cluster head selection and number of clusters. Modified Radial Based Neural Network is very simple, adaptable and efficient method to increase the life time of nodes, packet delivery ratio and the throughput of the network will increase and connection become more useful because the optimal path has the best parameters from other paths including the best bitrate and best life link with minimum delays. Proposed routing algorithm depends on the group of factors and parameters to select the path between two points in the wireless network. The SOM clustering average time (1-10 msec for stall nodes) and (8-75 msec for mobile nodes). While the routing time range (92-510 msec).The proposed system is faster than the Dijkstra by 150-300%, and faster from the RBFNN (without modify) by 145-180%.

Integrated circuit and method of arbitration in a network on an integrated circuit.

NARCIS (Netherlands)

2011-01-01

The invention relates to an integrated circuit and to a method of arbitration in a network on an integrated circuit. According to the invention, a method of arbitration in a network on an integrated circuit is provided, the network comprising a router unit, the router unit comprising a first input

QOS-aware error recovery in wireless body sensor networks using adaptive network coding.

Science.gov (United States)

Razzaque, Mohammad Abdur; Javadi, Saeideh S; Coulibaly, Yahaya; Hira, Muta Tah

2014-12-29

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

Phylogenetic comparative methods on phylogenetic networks with reticulations.

Science.gov (United States)

Bastide, Paul; Solís-Lemus, Claudia; Kriebel, Ricardo; Sparks, K William; Ané, Cécile

2018-04-25

The goal of Phylogenetic Comparative Methods (PCMs) is to study the distribution of quantitative traits among related species. The observed traits are often seen as the result of a Brownian Motion (BM) along the branches of a phylogenetic tree. Reticulation events such as hybridization, gene flow or horizontal gene transfer, can substantially affect a species' traits, but are not modeled by a tree. Phylogenetic networks have been designed to represent reticulate evolution. As they become available for downstream analyses, new models of trait evolution are needed, applicable to networks. One natural extension of the BM is to use a weighted average model for the trait of a hybrid, at a reticulation point. We develop here an efficient recursive algorithm to compute the phylogenetic variance matrix of a trait on a network, in only one preorder traversal of the network. We then extend the standard PCM tools to this new framework, including phylogenetic regression with covariates (or phylogenetic ANOVA), ancestral trait reconstruction, and Pagel's λ test of phylogenetic signal. The trait of a hybrid is sometimes outside of the range of its two parents, for instance because of hybrid vigor or hybrid depression. These two phenomena are rather commonly observed in present-day hybrids. Transgressive evolution can be modeled as a shift in the trait value following a reticulation point. We develop a general framework to handle such shifts, and take advantage of the phylogenetic regression view of the problem to design statistical tests for ancestral transgressive evolution in the evolutionary history of a group of species. We study the power of these tests in several scenarios, and show that recent events have indeed the strongest impact on the trait distribution of present-day taxa. We apply those methods to a dataset of Xiphophorus fishes, to confirm and complete previous analysis in this group. All the methods developed here are available in the Julia package PhyloNetworks.

BIMLR: a method for constructing rooted phylogenetic networks from rooted phylogenetic trees.

Science.gov (United States)

Wang, Juan; Guo, Maozu; Xing, Linlin; Che, Kai; Liu, Xiaoyan; Wang, Chunyu

2013-09-15

Rooted phylogenetic trees constructed from different datasets (e.g. from different genes) are often conflicting with one another, i.e. they cannot be integrated into a single phylogenetic tree. Phylogenetic networks have become an important tool in molecular evolution, and rooted phylogenetic networks are able to represent conflicting rooted phylogenetic trees. Hence, the development of appropriate methods to compute rooted phylogenetic networks from rooted phylogenetic trees has attracted considerable research interest of late. The CASS algorithm proposed by van Iersel et al. is able to construct much simpler networks than other available methods, but it is extremely slow, and the networks it constructs are dependent on the order of the input data. Here, we introduce an improved CASS algorithm, BIMLR. We show that BIMLR is faster than CASS and less dependent on the input data order. Moreover, BIMLR is able to construct much simpler networks than almost all other methods. BIMLR is available at http://nclab.hit.edu.cn/wangjuan/BIMLR/. © 2013 Elsevier B.V. All rights reserved.

Drug delivery matrices based on scleroglucan/alginate/borax gels.

Science.gov (United States)

Matricardi, Pietro; Onorati, Ilenia; Coviello, Tommasina; Alhaique, Franco

2006-06-19

The aim of this work is to obtain a new drug delivery matrix, especially designed for protein delivery, based on biodegradable and biocompatible polymers, and to describe its main physico-chemical properties. A polysaccharide based semi-interpenetrating polymer network (semi-IPN) was built up, composed by sodium alginate chains interspersed into a scleroglucan/borax hydrogel network. Tablets were obtained by compression of the resulting freeze-dried hydrogel. The different release and physico-chemical properties possessed by the two starting polymers in various aqueous media were combined in the new matrix. In this work, description is given of the in vitro ability of the matrix to deliver in a controlled manner a protein, Myoglobin, in distilled water, simulated gastric fluid and simulated intestinal fluid; the release, simulating a gastric passage, followed by an enteric delivery, was also carried out. Water uptake data, colorimetric experiments and scanning electron microscopy images are given for the characterization of this new solid dosage form; the importance of the borax presence is also discussed.

Human Detection System by Fusing Depth Map-Based Method and Convolutional Neural Network-Based Method

Directory of Open Access Journals (Sweden)

Anh Vu Le

2017-01-01

Full Text Available In this paper, the depth images and the colour images provided by Kinect sensors are used to enhance the accuracy of human detection. The depth-based human detection method is fast but less accurate. On the other hand, the faster region convolutional neural network-based human detection method is accurate but requires a rather complex hardware configuration. To simultaneously leverage the advantages and relieve the drawbacks of each method, one master and one client system is proposed. The final goal is to make a novel Robot Operation System (ROS-based Perception Sensor Network (PSN system, which is more accurate and ready for the real time application. The experimental results demonstrate the outperforming of the proposed method compared with other conventional methods in the challenging scenarios.

A systemic method for evaluating the potential impacts of floods on network infrastructures

Directory of Open Access Journals (Sweden)

J. Eleutério

2013-04-01

Full Text Available Understanding network infrastructures and their operation under exceptional circumstances is fundamental for dealing with flood risks and improving the resilience of a territory. This work presents a method for evaluating potential network infrastructure dysfunctions and damage in cases of flooding. In contrast to existing approaches, this method analyses network infrastructures on an elementary scale, by considering networks as a group of elements with specific functions and individual vulnerabilities. Our analysis places assets at the centre of the evaluation process, resulting in the construction of damage-dysfunction matrices based on expert interviews. These matrices permit summarising the different vulnerabilities of network infrastructures, describing how the different components are linked to each other and how they can disrupt the operation of the network. They also identify the actions and resources needed to restore the system to operational status following damage and dysfunctions, an essential point when dealing with the question of resilience. The method promotes multi-network analyses and is illustrated by a French case study. Sixty network experts were interviewed during the analysis of the following networks: drinking water supply, waste water, public lighting, gas distribution and electricity supply.

Classification Method in Integrated Information Network Using Vector Image Comparison

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Zhou Yuan

2014-05-01

Full Text Available Wireless Integrated Information Network (WMN consists of integrated information that can get data from its surrounding, such as image, voice. To transmit information, large resource is required which decreases the service time of the network. In this paper we present a Classification Approach based on Vector Image Comparison (VIC for WMN that improve the service time of the network. The available methods for sub-region selection and conversion are also proposed.

GeneNetWeaver: in silico benchmark generation and performance profiling of network inference methods.

Science.gov (United States)

Schaffter, Thomas; Marbach, Daniel; Floreano, Dario

2011-08-15

Over the last decade, numerous methods have been developed for inference of regulatory networks from gene expression data. However, accurate and systematic evaluation of these methods is hampered by the difficulty of constructing adequate benchmarks and the lack of tools for a differentiated analysis of network predictions on such benchmarks. Here, we describe a novel and comprehensive method for in silico benchmark generation and performance profiling of network inference methods available to the community as an open-source software called GeneNetWeaver (GNW). In addition to the generation of detailed dynamical models of gene regulatory networks to be used as benchmarks, GNW provides a network motif analysis that reveals systematic prediction errors, thereby indicating potential ways of improving inference methods. The accuracy of network inference methods is evaluated using standard metrics such as precision-recall and receiver operating characteristic curves. We show how GNW can be used to assess the performance and identify the strengths and weaknesses of six inference methods. Furthermore, we used GNW to provide the international Dialogue for Reverse Engineering Assessments and Methods (DREAM) competition with three network inference challenges (DREAM3, DREAM4 and DREAM5). GNW is available at http://gnw.sourceforge.net along with its Java source code, user manual and supporting data. Supplementary data are available at Bioinformatics online. dario.floreano@epfl.ch.

a Method for the Seamlines Network Automatic Selection Based on Building Vector

Science.gov (United States)

Li, P.; Dong, Y.; Hu, Y.; Li, X.; Tan, P.

2018-04-01

In order to improve the efficiency of large scale orthophoto production of city, this paper presents a method for automatic selection of seamlines network in large scale orthophoto based on the buildings' vector. Firstly, a simple model of the building is built by combining building's vector, height and DEM, and the imaging area of the building on single DOM is obtained. Then, the initial Voronoi network of the measurement area is automatically generated based on the positions of the bottom of all images. Finally, the final seamlines network is obtained by optimizing all nodes and seamlines in the network automatically based on the imaging areas of the buildings. The experimental results show that the proposed method can not only get around the building seamlines network quickly, but also remain the Voronoi network' characteristics of projection distortion minimum theory, which can solve the problem of automatic selection of orthophoto seamlines network in image mosaicking effectively.

Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

Science.gov (United States)

Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

2014-07-01

Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

Injectable shear-thinning nanoengineered hydrogels for stem cell delivery

DEFF Research Database (Denmark)

Thakur, Ashish; Jaiswal, Manish K.; Peak, Charles W.

2016-01-01

-thinning characteristics, and enhanced mechanical stiffness, elastomeric properties, and physiological stability. The shear-thinning characteristics of nanocomposite hydrogels are investigated for human mesenchymal stem cell (hMSC) delivery. The hMSCs showed high cell viability after injection and encapsulated cells......Injectable hydrogels are investigated for cell encapsulation and delivery as they can shield cells from high shear forces. One of the approaches to obtain injectable hydrogels is to reinforce polymeric networks with high aspect ratio nanoparticles such as two-dimensional (2D) nanomaterials. 2D...... showed a circular morphology. The proposed shear-thinning nanoengineered hydrogels can be used for cell delivery for cartilage tissue regeneration and 3D bioprinting....

Analytical maximum-likelihood method to detect patterns in real networks

International Nuclear Information System (INIS)

Squartini, Tiziano; Garlaschelli, Diego

2011-01-01

In order to detect patterns in real networks, randomized graph ensembles that preserve only part of the topology of an observed network are systematically used as fundamental null models. However, the generation of them is still problematic. Existing approaches are either computationally demanding and beyond analytic control or analytically accessible but highly approximate. Here, we propose a solution to this long-standing problem by introducing a fast method that allows one to obtain expectation values and standard deviations of any topological property analytically, for any binary, weighted, directed or undirected network. Remarkably, the time required to obtain the expectation value of any property analytically across the entire graph ensemble is as short as that required to compute the same property using the adjacency matrix of the single original network. Our method reveals that the null behavior of various correlation properties is different from what was believed previously, and is highly sensitive to the particular network considered. Moreover, our approach shows that important structural properties (such as the modularity used in community detection problems) are currently based on incorrect expressions, and provides the exact quantities that should replace them.

IP2P K-means: an efficient method for data clustering on sensor networks

Directory of Open Access Journals (Sweden)

Peyman Mirhadi

2013-03-01

Full Text Available Many wireless sensor network applications require data gathering as the most important parts of their operations. There are increasing demands for innovative methods to improve energy efficiency and to prolong the network lifetime. Clustering is considered as an efficient topology control methods in wireless sensor networks, which can increase network scalability and lifetime. This paper presents a method, IP2P K-means – Improved P2P K-means, which uses efficient leveling in clustering approach, reduces false labeling and restricts the necessary communication among various sensors, which obviously saves more energy. The proposed method is examined in Network Simulator Ver.2 (NS2 and the preliminary results show that the algorithm works effectively and relatively more precisely.

Research on the method of measuring space information network capacity in communication service

Directory of Open Access Journals (Sweden)

Zhu Shichao

2017-02-01

Full Text Available Because of the large scale characteristic of space information network in terms of space and time and the increasing of its complexity,existing measuring methods of information transmission capacity have been unable to measure the existing and future space information networkeffectively.In this study,we firstly established a complex model of space information network,and measured the whole space information network capacity by means of analyzing data access capability to the network and data transmission capability within the network.At last,we verified the rationality of the proposed measuring method by using STK and Matlab simulation software for collaborative simulation.

Fiber coupled optical spark delivery system

Science.gov (United States)

Yalin, Azer; Willson, Bryan; Defoort, Morgan

2008-08-12

A spark delivery system for generating a spark using a laser beam is provided, the spark delivery system including a laser light source and a laser delivery assembly. The laser delivery assembly includes a hollow fiber and a launch assembly comprising launch focusing optics to input the laser beam in the hollow fiber. In addition, the laser delivery assembly includes exit focusing optics that demagnify an exit beam of laser light from the hollow fiber, thereby increasing the intensity of the laser beam and creating a spark. In accordance with embodiments of the present invention, the assembly may be used to create a spark in a combustion engine. In accordance with other embodiments of the present invention, a method of using the spark delivery system is provided. In addition, a method of choosing an appropriate fiber for creating a spark using a laser beam is also presented.

A New Resilience Measure for Supply Chain Networks

Directory of Open Access Journals (Sweden)

Ruiying Li

2017-01-01

Full Text Available Currently, supply chain networks can span the whole world, and any disruption of these networks may cause economic losses, decreases in sales and unsustainable supplies. Resilience, the ability of the system to withstand disruption and return to a normal state quickly, has become a new challenge during the supply chain network design. This paper defines a new resilience measure as the ratio of the integral of the normalized system performance within its maximum allowable recovery time after the disruption to the integral of the performance in the normal state. Using the maximum allowable recovery time of the system as the time interval under consideration, this measure allows the resilience of different systems to be compared on the same relative scale, and be used under both scenarios that the system can or cannot restore in the given time. Two specific resilience measures, the resilience based on the amount of product delivered and the resilience based on the average delivery distance, are provided for supply chain networks. To estimate the resilience of a given supply chain network, a resilience simulation method is proposed based on the Monte Carlo method. A four-layered hierarchial mobile phone supply chain network is used to illustrate the resilience quantification process and show how network structure affects the resilience of supply chain networks.

Problem-Solving Methods for the Prospective Development of Urban Power Distribution Network

Directory of Open Access Journals (Sweden)

A. P. Karpenko

2014-01-01

Full Text Available This article succeeds the former A. P. K nko’ and A. I. Kuzmina’ ubl t on titled "A mathematical model of urban distribution electro-network considering its future development" (electronic scientific and technical magazine "Science and education" No. 5, 2014.The article offers a model of urban power distribution network as a set of transformer and distribution substations and cable lines. All elements of the network and new consumers are determined owing to vectors of parameters consistent with them.A problem of the urban power distribution network design, taking into account a prospective development of the city, is presented as a problem of discrete programming. It is in deciding on the optimal option to connect new consumers to the power supply network, on the number and sites to build new substations, and on the option to include them in the power supply network.Two methods, namely a reduction method for a set the nested tasks of global minimization and a decomposition method are offered to solve the problem.In reduction method the problem of prospective development of power supply network breaks into three subtasks of smaller dimension: a subtask to define the number and sites of new transformer and distribution substations, a subtask to define the option to connect new consumers to the power supply network, and a subtask to include new substations in the power supply network. The vector of the varied parameters is broken into three subvectors consistent with the subtasks. Each subtask is solved using an area of admissible vector values of the varied parameters at the fixed components of the subvectors obtained when solving the higher subtasks.In decomposition method the task is presented as a set of three, similar to reduction method, reductions of subtasks and a problem of coordination. The problem of coordination specifies a sequence of the subtasks solution, defines the moment of calculation termination. Coordination is realized by

Cellular Neural Network-Based Methods for Distributed Network Intrusion Detection

Directory of Open Access Journals (Sweden)

Kang Xie

2015-01-01

Full Text Available According to the problems of current distributed architecture intrusion detection systems (DIDS, a new online distributed intrusion detection model based on cellular neural network (CNN was proposed, in which discrete-time CNN (DTCNN was used as weak classifier in each local node and state-controlled CNN (SCCNN was used as global detection method, respectively. We further proposed a new method for design template parameters of SCCNN via solving Linear Matrix Inequality. Experimental results based on KDD CUP 99 dataset show its feasibility and effectiveness. Emerging evidence has indicated that this new approach is affordable to parallelism and analog very large scale integration (VLSI implementation which allows the distributed intrusion detection to be performed better.

QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

Science.gov (United States)

Razzaque, Mohammad Abdur; Javadi, Saeideh S.; Coulibaly, Yahaya; Hira, Muta Tah

2015-01-01

Wireless body sensor networks (WBSNs) for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS), in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network's QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts. PMID:25551485

A Grooming Nodes Optimal Allocation Method for Multicast in WDM Networks

Directory of Open Access Journals (Sweden)

Chengying Wei

2016-01-01

Full Text Available The grooming node has the capability of grooming multicast traffic with the small granularity into established light at high cost of complexity and node architecture. In the paper, a grooming nodes optimal allocation (GNOA method is proposed to optimize the allocation of the grooming nodes constraint by the blocking probability for multicast traffic in sparse WDM networks. In the proposed GNOA method, the location of each grooming node is determined by the SCLD strategy. The improved smallest cost largest degree (SCLD strategy is designed to select the nongrooming nodes in the proposed GNOA method. The simulation results show that the proposed GNOA method can reduce the required number of grooming nodes and decrease the cost of constructing a network to guarantee a certain request blocking probability when the wavelengths per fiber and transmitter/receiver ports per node are sufficient for the optical multicast in WDM networks.

Network Edge Intelligence for the Emerging Next-Generation Internet

Directory of Open Access Journals (Sweden)

Salekul Islam

2010-11-01

Full Text Available The success of the Content Delivery Networks (CDN in the recent years has demonstrated the increased benefits of the deployment of some form of “intelligence” within the network. Cloud computing, on the other hand, has shown the benefits of economies of scale and the use of a generic infrastructure to support a variety of services. Following that trend, we propose to move away from the smart terminal-dumb network dichotomy to a model where some degree of intelligence is put back into the network, specifically at the edge, with the support of Cloud technology. In this paper, we propose the deployment of an Edge Cloud, which integrates a variety of user-side and server-side services. On the user side, surrogate, an application running on top of the Cloud, supports a virtual client. The surrogate hides the underlying network infrastructure from the user, thus allowing for simpler, more easily managed terminals. Network side services supporting delivery of and exploiting content are also deployed on this infrastructure, giving the Internet Service Providers (ISP many opportunities to become directly involved in content and service delivery.

A Novel Message Scheduling Framework for Delay Tolerant Networks Routing

KAUST Repository

Elwhishi, Ahmed

2013-05-01

Multicopy routing strategies have been considered the most applicable approaches to achieve message delivery in Delay Tolerant Networks (DTNs). Epidemic routing and two-hop forwarding routing are two well-reported approaches for delay tolerant networks routing which allow multiple message replicas to be launched in order to increase message delivery ratio and/or reduce message delivery delay. This advantage, nonetheless, is at the expense of additional buffer space and bandwidth overhead. Thus, to achieve efficient utilization of network resources, it is important to come up with an effective message scheduling strategy to determine which messages should be forwarded and which should be dropped in case of buffer is full. This paper investigates a new message scheduling framework for epidemic and two-hop forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. Extensive simulation results show that the proposed message scheduling framework can achieve better performance than its counterparts.

A hybrid network-based method for the detection of disease-related genes

Science.gov (United States)

Cui, Ying; Cai, Meng; Dai, Yang; Stanley, H. Eugene

2018-02-01

Detecting disease-related genes is crucial in disease diagnosis and drug design. The accepted view is that neighbors of a disease-causing gene in a molecular network tend to cause the same or similar diseases, and network-based methods have been recently developed to identify novel hereditary disease-genes in available biomedical networks. Despite the steady increase in the discovery of disease-associated genes, there is still a large fraction of disease genes that remains under the tip of the iceberg. In this paper we exploit the topological properties of the protein-protein interaction (PPI) network to detect disease-related genes. We compute, analyze, and compare the topological properties of disease genes with non-disease genes in PPI networks. We also design an improved random forest classifier based on these network topological features, and a cross-validation test confirms that our method performs better than previous similar studies.

Maximum entropy methods for extracting the learned features of deep neural networks.

Science.gov (United States)

Finnegan, Alex; Song, Jun S

2017-10-01

New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.

To share or not to share? Business aspects of network sharing for Mobile Network Operators

NARCIS (Netherlands)

Berkers, F.T.H.M.; Hendrix, G.; Chatzicharistou, I.; Haas, T. de; Hamera, D.

2010-01-01

Radio spectrum and network infrastructure are two essential resources for mobile service delivery, which are both costly and increasingly scarce. In this paper we consider drivers and barriers of network sharing, which is seen as a potential solution for scarcity in these resources. We considered a

Facile method of building hydroxyapatite 3D scaffolds assembled from porous hollow fibers enabling nutrient delivery

NARCIS (Netherlands)

Salamon, David; Da Silva Teixeira, Sandra; Dutczak, S.M.; Stamatialis, Dimitrios

2014-01-01

Nowadays, diffusion through scaffold and tissue usually limits transport, and forms potentially hypoxic regions. Several methods are used for preparation of 3D hydroxyapatite scaffolds, however, production of a scaffold including porous hollow fibers for nutrition delivery is difficult and

New knowledge network evaluation method for design rationale management

Science.gov (United States)

Jing, Shikai; Zhan, Hongfei; Liu, Jihong; Wang, Kuan; Jiang, Hao; Zhou, Jingtao

2015-01-01

Current design rationale (DR) systems have not demonstrated the value of the approach in practice since little attention is put to the evaluation method of DR knowledge. To systematize knowledge management process for future computer-aided DR applications, a prerequisite is to provide the measure for the DR knowledge. In this paper, a new knowledge network evaluation method for DR management is presented. The method characterizes the DR knowledge value from four perspectives, namely, the design rationale structure scale, association knowledge and reasoning ability, degree of design justification support and degree of knowledge representation conciseness. The DR knowledge comprehensive value is also measured by the proposed method. To validate the proposed method, different style of DR knowledge network and the performance of the proposed measure are discussed. The evaluation method has been applied in two realistic design cases and compared with the structural measures. The research proposes the DR knowledge evaluation method which can provide object metric and selection basis for the DR knowledge reuse during the product design process. In addition, the method is proved to be more effective guidance and support for the application and management of DR knowledge.

Synthesis and Characterization of Poly(hydroxyethyl methacrylate-co-methacrylic acid) Cross Linked Polymeric Network for the Delivery of Analgesic Agent

International Nuclear Information System (INIS)

Rashid, H.; Ahmad, M.; Minhas, M. U.; Aamir, M. F.; Sohail, M.

2015-01-01

Objective of the study was to synthesize a chemically cross-linked poly(hydroxyethylmethacrylate-co-methacrylic acid) hydrogel (p(HEMA-co-MAA hydrogel)) for pH-responsive, controlled drug delivery of Flurbiprofen. pH-sensitive hydrogel drug delivery system was synthesized with the help of poly hydroxyethyl methacrylate (HEMA) and methacrylic acid (MAA) by using ethylene glycol dimethacrylate (EGDMA) as crosslinker. The monomers (HEMA and MAA) were successfully cross linked through free radical polymerization process, initiated by benzoyl peroxide in an aqueous medium. All formulations were loaded with Flurbiprofen as a model drug and evaluated at pH 1.2 and pH 7.4 to investigate pH-responsive nature of the system. Fourier transform infrared spectroscopy (FTIR) was performed to confirm the cross-linking of copolymer while thermo gravimetric analysis (TGA) and differential scanning calorimetry (DSC) were performed to evaluate the thermal stability of the system. Swelling studies and in-vitro release studies were carried out to evaluate pH-responsive nature of the hydrogels. FTIR confirmed that monomers were successfully cross-linked to form a copolymer. Hydrogel system showed less swelling at lower pH while at higher pH, it showed higher swelling, releasing drug in the same fashion. It was concluded that a stable hydrogel network was chemically cross-linked showing pH-responsive nature and thus, synthesized p(HEMA-co-MAA) hydrogels can be successfully employed as potential candidate for controlled drug delivery. (author)

Real-time method for establishing a detection map for a network of sensors

Science.gov (United States)

Nguyen, Hung D; Koch, Mark W; Giron, Casey; Rondeau, Daniel M; Russell, John L

2012-09-11

A method for establishing a detection map of a dynamically configurable sensor network. This method determines an appropriate set of locations for a plurality of sensor units of a sensor network and establishes a detection map for the network of sensors while the network is being set up; the detection map includes the effects of the local terrain and individual sensor performance. Sensor performance is characterized during the placement of the sensor units, which enables dynamic adjustment or reconfiguration of the placement of individual elements of the sensor network during network set-up to accommodate variations in local terrain and individual sensor performance. The reconfiguration of the network during initial set-up to accommodate deviations from idealized individual sensor detection zones improves the effectiveness of the sensor network in detecting activities at a detection perimeter and can provide the desired sensor coverage of an area while minimizing unintentional gaps in coverage.

PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks.

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Thong Pham

Full Text Available Preferential attachment is a stochastic process that has been proposed to explain certain topological features characteristic of complex networks from diverse domains. The systematic investigation of preferential attachment is an important area of research in network science, not only for the theoretical matter of verifying whether this hypothesized process is operative in real-world networks, but also for the practical insights that follow from knowledge of its functional form. Here we describe a maximum likelihood based estimation method for the measurement of preferential attachment in temporal complex networks. We call the method PAFit, and implement it in an R package of the same name. PAFit constitutes an advance over previous methods primarily because we based it on a nonparametric statistical framework that enables attachment kernel estimation free of any assumptions about its functional form. We show this results in PAFit outperforming the popular methods of Jeong and Newman in Monte Carlo simulations. What is more, we found that the application of PAFit to a publically available Flickr social network dataset yielded clear evidence for a deviation of the attachment kernel from the popularly assumed log-linear form. Independent of our main work, we provide a correction to a consequential error in Newman's original method which had evidently gone unnoticed since its publication over a decade ago.

A method for estimation of accuracy of dose delivery with dynamic slit windows in medical linear accelerators

International Nuclear Information System (INIS)

Ravichandran, R.; Binukumar, J.P.; Sivakumar, S.S.; Krishnamurthy, K.; Davis, C.A.

2008-01-01

Intensity-modulated radiotherapy (IMRT) clinical dose delivery is based on computer-controlled multileaf movements at different velocities. To test the accuracy of modulation of the beam periodically, quality assurance (QA) methods are necessary. Using a cylindrical phantom, dose delivery was checked at a constant geometry for sweeping fields. Repeated measurements with an in-house designed methodology over a period of 1 year indicate that the method is very sensitive to check the proper functioning of such dose delivery in medical linacs. A cylindrical perspex phantom with facility to accurately position a 0.6- cc (FC 65) ion chamber at constant depth at isocenter, (SA 24 constancy check tool phantom for MU check, Scanditronix Wellhofer) was used. Dosimeter readings were integrated for 4-mm, 10-mm, 20-mm sweeping fields and for 3 angular positions of the gantry periodically. Consistency of standard sweeping field output (10-mm slit width) and the ratios of outputs against other slit widths over a long period were reported. A 10-mm sweeping field output was found reproducible within an accuracy of 0.03% (n = 25) over 1 year. Four-millimeter, 20-mm outputs expressed as ratio with respect to 10- mm sweep output remained within a mean deviation of 0.2% and 0.03% respectively. Outputs at 3 gantry angles remained within 0.5%, showing that the effect of dynamic movements of multileaf collimator (MLC) on the output is minimal for angular positions of gantry. This method of QA is very simple and is recommended in addition to individual patient QA measurements, which reflect the accuracy of dose planning system. In addition to standard output and energy checks of linacs, the above measurements can be complemented so as to check proper functioning of multileaf collimator for dynamic field dose delivery. (author)

Inversion of Density Interfaces Using the Pseudo-Backpropagation Neural Network Method

Science.gov (United States)

Chen, Xiaohong; Du, Yukun; Liu, Zhan; Zhao, Wenju; Chen, Xiaocheng

2018-05-01

This paper presents a new pseudo-backpropagation (BP) neural network method that can invert multi-density interfaces at one time. The new method is based on the conventional forward modeling and inverse modeling theories in addition to conventional pseudo-BP neural network arithmetic. A 3D inversion model for gravity anomalies of multi-density interfaces using the pseudo-BP neural network method is constructed after analyzing the structure and function of the artificial neural network. The corresponding iterative inverse formula of the space field is presented at the same time. Based on trials of gravity anomalies and density noise, the influence of the two kinds of noise on the inverse result is discussed and the scale of noise requested for the stability of the arithmetic is analyzed. The effects of the initial model on the reduction of the ambiguity of the result and improvement of the precision of inversion are discussed. The correctness and validity of the method were verified by the 3D model of the three interfaces. 3D inversion was performed on the observed gravity anomaly data of the Okinawa trough using the program presented herein. The Tertiary basement and Moho depth were obtained from the inversion results, which also testify the adaptability of the method. This study has made a useful attempt for the inversion of gravity density interfaces.

Preisach hysteresis implementation in reluctance network method, comparison with finite element method

OpenAIRE

Allag , Hicham; Kedous-Lebouc , Afef; Latreche , Mohamed E. H.

2008-01-01

International audience; In this work, an implementation of static magnetic hysteresis in the reluctance network method is presented and its effectiveness is demonstrated. This implementation is achieved by a succession of iterative steps in the form of algorithm explained and developed for simple examples. However it remains valid for any magnetic circuit. The results obtained are compared to those given by finite element method simulation and essentially the effect of relaxation is discussed...

Modeling community succession and assembly: A novel method for network evolution

Directory of Open Access Journals (Sweden)

WenJun Zhang

2012-06-01

Full Text Available The process of modeling community succession and assembly is in some sense a method for network evolution, as done by Barabasi and Albert (1999. It is also one of the methods to create a sample networkfrom the statistic network I proposed earlier. I think that the mechanism of network evolution supposed by Barabasi and Albert is most likely applicable to the natural phenomena with emergency property. For natural phenomena without emergency property, the present study indicated that a scale-free network may be produced through a new mechanism, i.e., whether the connection of a taxon x occurs, dependent on the type and property of taxon y (in particular, the degree of its direct correlation with x to be connected but not necessarily the existing number of connections of taxon y, as proposed in present study.

LON Technology in Wireless Sensor Networking Applications

Directory of Open Access Journals (Sweden)

Ryszard Golanski

2006-01-01

Full Text Available In the paper a discussion on how to optimize LonWorks/EIA-709 sensornetworking technology for wireless applications, in presented. Main solutions offered byLocal Operating Networks (LON, LonWorks platform attractive for wirelesscommunication, that is, the send-on-delta concept and the sleep mode, are displayed. Thepredictive p-persistent CSMA MAC protocol constituting the heart of the communicationcapability of LON networks is analysed in detail. Next, the message services are described,and the analytical evaluation of delivery reliability is derived. Performance evaluation basedon simulation results for unicast traffic is presented first. In order to highlight the robustnessof the predictive CSMA to overload situations, the saturation performance for a general caseload scenario including multicast transactions is reported. The methods of effectivemanagement of energy consumption in LonWorks networks are discussed. Finally, the LONdesign tradeoffs are summarized.

QoS-Aware Error Recovery in Wireless Body Sensor Networks Using Adaptive Network Coding

Directory of Open Access Journals (Sweden)

Mohammad Abdur Razzaque

2014-12-01

Full Text Available Wireless body sensor networks (WBSNs for healthcare and medical applications are real-time and life-critical infrastructures, which require a strict guarantee of quality of service (QoS, in terms of latency, error rate and reliability. Considering the criticality of healthcare and medical applications, WBSNs need to fulfill users/applications and the corresponding network’s QoS requirements. For instance, for a real-time application to support on-time data delivery, a WBSN needs to guarantee a constrained delay at the network level. A network coding-based error recovery mechanism is an emerging mechanism that can be used in these systems to support QoS at very low energy, memory and hardware cost. However, in dynamic network environments and user requirements, the original non-adaptive version of network coding fails to support some of the network and user QoS requirements. This work explores the QoS requirements of WBSNs in both perspectives of QoS. Based on these requirements, this paper proposes an adaptive network coding-based, QoS-aware error recovery mechanism for WBSNs. It utilizes network-level and user-/application-level information to make it adaptive in both contexts. Thus, it provides improved QoS support adaptively in terms of reliability, energy efficiency and delay. Simulation results show the potential of the proposed mechanism in terms of adaptability, reliability, real-time data delivery and network lifetime compared to its counterparts.

Optimized star sensors laboratory calibration method using a regularization neural network.

Science.gov (United States)

Zhang, Chengfen; Niu, Yanxiong; Zhang, Hao; Lu, Jiazhen

2018-02-10

High-precision ground calibration is essential to ensure the performance of star sensors. However, the complex distortion and multi-error coupling have brought great difficulties to traditional calibration methods, especially for large field of view (FOV) star sensors. Although increasing the complexity of models is an effective way to improve the calibration accuracy, it significantly increases the demand for calibration data. In order to achieve high-precision calibration of star sensors with large FOV, a novel laboratory calibration method based on a regularization neural network is proposed. A multi-layer structure neural network is designed to represent the mapping of the star vector and the corresponding star point coordinate directly. To ensure the generalization performance of the network, regularization strategies are incorporated into the net structure and the training algorithm. Simulation and experiment results demonstrate that the proposed method can achieve high precision with less calibration data and without any other priori information. Compared with traditional methods, the calibration error of the star sensor decreased by about 30%. The proposed method can satisfy the precision requirement for large FOV star sensors.

Mucus as a Barrier to Drug Delivery

DEFF Research Database (Denmark)

Bøgh, Marie; Nielsen, Hanne Mørck

2015-01-01

Viscoelastic mucus lines all mucosal surfaces of the body and forms a potential barrier to mucosal drug delivery. Mucus is mainly composed of water and mucins; high-molecular weight glycoproteins forming an entangled network. Consequently, mucus forms a steric barrier and due to its negative charge...... barrier to drug delivery. Current knowledge of mucus characteristics and barrier properties, as achieved by state-of-the-art methodologies, is the topic of this MiniReview emphasizing the gastrointestinal mucus and an overall focus on oral drug delivery. Cell culture-based in vitro models are well......, studies of peptide and protein drug diffusion in and through mucus and studies of mucus-penetrating nanoparticles are included to illustrate the mucus as a potentially important barrier to obtain sufficient bioavailability of orally administered drugs, and thus an important parameter to address...

msiDBN: A Method of Identifying Critical Proteins in Dynamic PPI Networks

Directory of Open Access Journals (Sweden)

Yuan Zhang

2014-01-01

Full Text Available Dynamics of protein-protein interactions (PPIs reveals the recondite principles of biological processes inside a cell. Shown in a wealth of study, just a small group of proteins, rather than the majority, play more essential roles at crucial points of biological processes. This present work focuses on identifying these critical proteins exhibiting dramatic structural changes in dynamic PPI networks. First, a comprehensive way of modeling the dynamic PPIs is presented which simultaneously analyzes the activity of proteins and assembles the dynamic coregulation correlation between proteins at each time point. Second, a novel method is proposed, named msiDBN, which models a common representation of multiple PPI networks using a deep belief network framework and analyzes the reconstruction errors and the variabilities across the time courses in the biological process. Experiments were implemented on data of yeast cell cycles. We evaluated our network construction method by comparing the functional representations of the derived networks with two other traditional construction methods. The ranking results of critical proteins in msiDBN were compared with the results from the baseline methods. The results of comparison showed that msiDBN had better reconstruction rate and identified more proteins of critical value to yeast cell cycle process.

The QAP weighted network analysis method and its application in international services trade

Science.gov (United States)

Xu, Helian; Cheng, Long

2016-04-01

Based on QAP (Quadratic Assignment Procedure) correlation and complex network theory, this paper puts forward a new method named QAP Weighted Network Analysis Method. The core idea of the method is to analyze influences among relations in a social or economic group by building a QAP weighted network of networks of relations. In the QAP weighted network, a node depicts a relation and an undirect edge exists between any pair of nodes if there is significant correlation between relations. As an application of the QAP weighted network, we study international services trade by using the QAP weighted network, in which nodes depict 10 kinds of services trade relations. After the analysis of international services trade by QAP weighted network, and by using distance indicators, hierarchy tree and minimum spanning tree, the conclusion shows that: Firstly, significant correlation exists in all services trade, and the development of any one service trade will stimulate the other nine. Secondly, as the economic globalization goes deeper, correlations in all services trade have been strengthened continually, and clustering effects exist in those services trade. Thirdly, transportation services trade, computer and information services trade and communication services trade have the most influence and are at the core in all services trade.

Hybrid digital signal processing and neural networks for automated diagnostics using NDE methods

International Nuclear Information System (INIS)

Upadhyaya, B.R.; Yan, W.

1993-11-01

The primary purpose of the current research was to develop an integrated approach by combining information compression methods and artificial neural networks for the monitoring of plant components using nondestructive examination data. Specifically, data from eddy current inspection of heat exchanger tubing were utilized to evaluate this technology. The focus of the research was to develop and test various data compression methods (for eddy current data) and the performance of different neural network paradigms for defect classification and defect parameter estimation. Feedforward, fully-connected neural networks, that use the back-propagation algorithm for network training, were implemented for defect classification and defect parameter estimation using a modular network architecture. A large eddy current tube inspection database was acquired from the Metals and Ceramics Division of ORNL. These data were used to study the performance of artificial neural networks for defect type classification and for estimating defect parameters. A PC-based data preprocessing and display program was also developed as part of an expert system for data management and decision making. The results of the analysis showed that for effective (low-error) defect classification and estimation of parameters, it is necessary to identify proper feature vectors using different data representation methods. The integration of data compression and artificial neural networks for information processing was established as an effective technique for automation of diagnostics using nondestructive examination methods

Load management in electrical networks. Objectives, methods, prospects

International Nuclear Information System (INIS)

Gabioud, D.

2008-01-01

This illustrated article takes up the problems related to the variation of the load in electricity networks. How to handle the peak load? Different solutions in the energy demand management are discussed. Method based on the price, method based on the reduction of the load by electric utilities. Information systems are presented which gives the consumer the needed data to participate in the local load management.

Use of a mobile social networking intervention for weight management: a mixed-methods study protocol.

Science.gov (United States)

Laranjo, Liliana; Lau, Annie Y S; Martin, Paige; Tong, Huong Ly; Coiera, Enrico

2017-07-12

Obesity and physical inactivity are major societal challenges and significant contributors to the global burden of disease and healthcare costs. Information and communication technologies are increasingly being used in interventions to promote behaviour change in diet and physical activity. In particular, social networking platforms seem promising for the delivery of weight control interventions.We intend to pilot test an intervention involving the use of a social networking mobile application and tracking devices ( Fitbit Flex 2 and Fitbit Aria scale) to promote the social comparison of weight and physical activity, in order to evaluate whether mechanisms of social influence lead to changes in those outcomes over the course of the study. Mixed-methods study involving semi-structured interviews and a pre-post quasi-experimental pilot with one arm, where healthy participants in different body mass index (BMI) categories, aged between 19 and 35 years old, will be subjected to a social networking intervention over a 6-month period. The primary outcome is the average difference in weight before and after the intervention. Secondary outcomes include BMI, number of steps per day, engagement with the intervention, social support and system usability. Semi-structured interviews will assess participants' expectations and perceptions regarding the intervention. Ethics approval was granted by Macquarie University's Human Research Ethics Committee for Medical Sciences on 3 November 2016 (ethics reference number 5201600716).The social network will be moderated by a researcher with clinical expertise, who will monitor and respond to concerns raised by participants. Monitoring will involve daily observation of measures collected by the fitness tracker and the wireless scale, as well as continuous supervision of forum interactions and posts. Additionally, a protocol is in place to monitor for participant misbehaviour and direct participants-in-need to appropriate sources of help

Review of Congestion Management Methods for Distribution Networks with High Penetration of Distributed Energy Resources

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Liu, Zhaoxi

2014-01-01

This paper reviews the existing congestion management methods for distribution networks with high penetration of DERs documented in the recent research literatures. The congestion management methods for distribution networks reviewed can be grouped into two categories – market methods and direct...... control methods. The market methods consist of dynamic tariff, distribution capacity market, shadow price and flexible service market. The direct control methods are comprised of network reconfiguration, reactive power control and active power control. Based on the review of the existing methods...

Boundedness and convergence of online gradient method with penalty for feedforward neural networks.

Science.gov (United States)

Zhang, Huisheng; Wu, Wei; Liu, Fei; Yao, Mingchen

2009-06-01

In this brief, we consider an online gradient method with penalty for training feedforward neural networks. Specifically, the penalty is a term proportional to the norm of the weights. Its roles in the method are to control the magnitude of the weights and to improve the generalization performance of the network. By proving that the weights are automatically bounded in the network training with penalty, we simplify the conditions that are required for convergence of online gradient method in literature. A numerical example is given to support the theoretical analysis.

Unified pipe network method for simulation of water flow in fractured porous rock

Science.gov (United States)

Ren, Feng; Ma, Guowei; Wang, Yang; Li, Tuo; Zhu, Hehua

2017-04-01

Rock masses are often conceptualized as dual-permeability media containing fractures or fracture networks with high permeability and porous matrix that is less permeable. In order to overcome the difficulties in simulating fluid flow in a highly discontinuous dual-permeability medium, an effective unified pipe network method is developed, which discretizes the dual-permeability rock mass into a virtual pipe network system. It includes fracture pipe networks and matrix pipe networks. They are constructed separately based on equivalent flow models in a representative area or volume by taking the advantage of the orthogonality of the mesh partition. Numerical examples of fluid flow in 2-D and 3-D domain including porous media and fractured porous media are presented to demonstrate the accuracy, robustness, and effectiveness of the proposed unified pipe network method. Results show that the developed method has good performance even with highly distorted mesh. Water recharge into the fractured rock mass with complex fracture network is studied. It has been found in this case that the effect of aperture change on the water recharge rate is more significant in the early stage compared to the fracture density change.

Statistical and optimization methods to expedite neural network training for transient identification

International Nuclear Information System (INIS)

Reifman, J.; Vitela, E.J.; Lee, J.C.

1993-01-01

Two complementary methods, statistical feature selection and nonlinear optimization through conjugate gradients, are used to expedite feedforward neural network training. Statistical feature selection techniques in the form of linear correlation coefficients and information-theoretic entropy are used to eliminate redundant and non-informative plant parameters to reduce the size of the network. The method of conjugate gradients is used to accelerate the network training convergence and to systematically calculate the Teaming and momentum constants at each iteration. The proposed techniques are compared with the backpropagation algorithm using the entire set of plant parameters in the training of neural networks to identify transients simulated with the Midland Nuclear Power Plant Unit 2 simulator. By using 25% of the plant parameters and the conjugate gradients, a 30-fold reduction in CPU time was obtained without degrading the diagnostic ability of the network

Network-based ranking methods for prediction of novel disease associated microRNAs.

Science.gov (United States)

Le, Duc-Hau

2015-10-01

Many studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a "disease module" principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the "disease module" principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction. We constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm. Analyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In

A rapid reliability estimation method for directed acyclic lifeline networks with statistically dependent components

International Nuclear Information System (INIS)

Kang, Won-Hee; Kliese, Alyce

2014-01-01

Lifeline networks, such as transportation, water supply, sewers, telecommunications, and electrical and gas networks, are essential elements for the economic and societal functions of urban areas, but their components are highly susceptible to natural or man-made hazards. In this context, it is essential to provide effective pre-disaster hazard mitigation strategies and prompt post-disaster risk management efforts based on rapid system reliability assessment. This paper proposes a rapid reliability estimation method for node-pair connectivity analysis of lifeline networks especially when the network components are statistically correlated. Recursive procedures are proposed to compound all network nodes until they become a single super node representing the connectivity between the origin and destination nodes. The proposed method is applied to numerical network examples and benchmark interconnected power and water networks in Memphis, Shelby County. The connectivity analysis results show the proposed method's reasonable accuracy and remarkable efficiency as compared to the Monte Carlo simulations

Freeze-dried, mucoadhesive system for vaginal delivery of the HIV microbicide, dapivirine: optimisation by an artificial neural network.

Science.gov (United States)

Woolfson, A David; Umrethia, Manish L; Kett, Victoria L; Malcolm, R Karl

2010-03-30

Dapivirine mucoadhesive gels and freeze-dried tablets were prepared using a 3x3x2 factorial design. An artificial neural network (ANN) with multi-layer perception was used to investigate the effect of hydroxypropyl-methylcellulose (HPMC): polyvinylpyrrolidone (PVP) ratio (X1), mucoadhesive concentration (X2) and delivery system (gel or freeze-dried mucoadhesive tablet, X3) on response variables; cumulative release of dapivirine at 24h (Q(24)), mucoadhesive force (F(max)) and zero-rate viscosity. Optimisation was performed by minimising the error between the experimental and predicted values of responses by ANN. The method was validated using check point analysis by preparing six formulations of gels and their corresponding freeze-dried tablets randomly selected from within the design space of contour plots. Experimental and predicted values of response variables were not significantly different (p>0.05, two-sided paired t-test). For gels, Q(24) values were higher than their corresponding freeze-dried tablets. F(max) values for freeze-dried tablets were significantly different (2-4 times greater, p>0.05, two-sided paired t-test) compared to equivalent gels. Freeze-dried tablets having lower values for X1 and higher values for X2 components offered the best compromise between effective dapivirine release, mucoadhesion and viscosity such that increased vaginal residence time was likely to be achieved. Copyright (c) 2009 Elsevier B.V. All rights reserved.

Exploring Normalization and Network Reconstruction Methods using In Silico and In Vivo Models

Science.gov (United States)

Abstract: Lessons learned from the recent DREAM competitions include: The search for the best network reconstruction method continues, and we need more complete datasets with ground truth from more complex organisms. It has become obvious that the network reconstruction methods t...

Method Accelerates Training Of Some Neural Networks

Science.gov (United States)

Shelton, Robert O.

1992-01-01

Three-layer networks trained faster provided two conditions are satisfied: numbers of neurons in layers are such that majority of work done in synaptic connections between input and hidden layers, and number of neurons in input layer at least as great as number of training pairs of input and output vectors. Based on modified version of back-propagation method.

Transportation risk management : international practices for program development and project delivery.

Science.gov (United States)

2012-08-01

Managing transportation networks, including agency : management, program development, and project : delivery, is extremely complex and fraught with : uncertainty. Administrators, planners, and engineers : coordinate a multitude of organizational and ...

The Impact of Nutrition Information Delivery Methods on Restaurant Consumers' Attitudes and Behavior

OpenAIRE

Zhu, Jiaqi

2013-01-01

Zhu, Jiaqi. M.S., Purdue University, December 2013. The Impact of Nutrition Information Delivery Methods on Restaurant Consumers' Attitudes and Behavior. Major Professors: Barbara A. Almanza, Carl A. Behnke. Obesity is a major public health threat. It not only creates challenges for those who are obese and overweight, but also brings an economic burden to the whole society. One important contributing factor for obesity is food eaten away from home, which accounts for more than 40% of Ameri...

Cell and biomolecule delivery for regenerative medicine

Science.gov (United States)

Smith, Ian O; Ma, Peter X

2010-01-01

Regenerative medicine is an exciting field that aims to create regenerative alternatives to harvest tissues for transplantation. In this approach, the delivery of cells and biological molecules plays a central role. The scaffold (synthetic temporary extracellular matrix) delivers cells to the regenerative site and provides three-dimensional environments for the cells. To fulfil these functions, we design biodegradable polymer scaffolds with structural features on multiple size scales. To enhance positive cell–material interactions, we design nano-sized structural features in the scaffolds to mimic the natural extracellular matrix. We also integrate micro-sized pore networks to facilitate mass transport and neo tissue regeneration. We also design novel polymer devices and self-assembled nanospheres for biomolecule delivery to recapitulate key events in developmental and wound healing processes. Herein, we present recent work in biomedical polymer synthesis, novel processing techniques, surface engineering and biologic delivery. Examples of enhanced cellular/tissue function and regenerative outcomes of these approaches are discussed to demonstrate the excitement of the biomimetic scaffold design and biologic delivery in regenerative medicine. PMID:27877317

A novel mutual information-based Boolean network inference method from time-series gene expression data.

Directory of Open Access Journals (Sweden)

Shohag Barman

Full Text Available Inferring a gene regulatory network from time-series gene expression data in systems biology is a challenging problem. Many methods have been suggested, most of which have a scalability limitation due to the combinatorial cost of searching a regulatory set of genes. In addition, they have focused on the accurate inference of a network structure only. Therefore, there is a pressing need to develop a network inference method to search regulatory genes efficiently and to predict the network dynamics accurately.In this study, we employed a Boolean network model with a restricted update rule scheme to capture coarse-grained dynamics, and propose a novel mutual information-based Boolean network inference (MIBNI method. Given time-series gene expression data as an input, the method first identifies a set of initial regulatory genes using mutual information-based feature selection, and then improves the dynamics prediction accuracy by iteratively swapping a pair of genes between sets of the selected regulatory genes and the other genes. Through extensive simulations with artificial datasets, MIBNI showed consistently better performance than six well-known existing methods, REVEAL, Best-Fit, RelNet, CST, CLR, and BIBN in terms of both structural and dynamics prediction accuracy. We further tested the proposed method with two real gene expression datasets for an Escherichia coli gene regulatory network and a fission yeast cell cycle network, and also observed better results using MIBNI compared to the six other methods.Taken together, MIBNI is a promising tool for predicting both the structure and the dynamics of a gene regulatory network.

Engaging Faculty in Telecommunications-Based Instructional Delivery Systems.

Science.gov (United States)

Swalec, John J.

In the design and development of telecommunications-based instructional delivery systems, attention to faculty involvement and training is often overlooked until the system is operational. The Waubonsee Telecommunications Instructional Consortium (TIC), in Illinois, is one network that benefited from early faculty input. Even before the first…

Methods for Inferring Health-Related Social Networks among Coworkers from Online Communication Patterns

Science.gov (United States)

Matthews, Luke J.; DeWan, Peter; Rula, Elizabeth Y.

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network. PMID

Methods for inferring health-related social networks among coworkers from online communication patterns.

Directory of Open Access Journals (Sweden)

Luke J Matthews

Full Text Available Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1 the absolute number of emails exchanged, (2 logistic regression probability of an offline relationship, and (3 the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a

Methods for inferring health-related social networks among coworkers from online communication patterns.

Science.gov (United States)

Matthews, Luke J; DeWan, Peter; Rula, Elizabeth Y

2013-01-01

Studies of social networks, mapped using self-reported contacts, have demonstrated the strong influence of social connections on the propensity for individuals to adopt or maintain healthy behaviors and on their likelihood to adopt health risks such as obesity. Social network analysis may prove useful for businesses and organizations that wish to improve the health of their populations by identifying key network positions. Health traits have been shown to correlate across friendship ties, but evaluating network effects in large coworker populations presents the challenge of obtaining sufficiently comprehensive network data. The purpose of this study was to evaluate methods for using online communication data to generate comprehensive network maps that reproduce the health-associated properties of an offline social network. In this study, we examined three techniques for inferring social relationships from email traffic data in an employee population using thresholds based on: (1) the absolute number of emails exchanged, (2) logistic regression probability of an offline relationship, and (3) the highest ranked email exchange partners. As a model of the offline social network in the same population, a network map was created using social ties reported in a survey instrument. The email networks were evaluated based on the proportion of survey ties captured, comparisons of common network metrics, and autocorrelation of body mass index (BMI) across social ties. Results demonstrated that logistic regression predicted the greatest proportion of offline social ties, thresholding on number of emails exchanged produced the best match to offline network metrics, and ranked email partners demonstrated the strongest autocorrelation of BMI. Since each method had unique strengths, researchers should choose a method based on the aspects of offline behavior of interest. Ranked email partners may be particularly useful for purposes related to health traits in a social network.

Microfabrication for Drug Delivery

Science.gov (United States)

Koch, Brendan; Rubino, Ilaria; Quan, Fu-Shi; Yoo, Bongyoung; Choi, Hyo-Jick

2016-01-01

This review is devoted to discussing the application of microfabrication technologies to target challenges encountered in life processes by the development of drug delivery systems. Recently, microfabrication has been largely applied to solve health and pharmaceutical science issues. In particular, fabrication methods along with compatible materials have been successfully designed to produce multifunctional, highly effective drug delivery systems. Microfabrication offers unique tools that can tackle problems in this field, such as ease of mass production with high quality control and low cost, complexity of architecture design and a broad range of materials. Presented is an overview of silicon- and polymer-based fabrication methods that are key in the production of microfabricated drug delivery systems. Moreover, the efforts focused on studying the biocompatibility of materials used in microfabrication are analyzed. Finally, this review discusses representative ways microfabrication has been employed to develop systems delivering drugs through the transdermal and oral route, and to improve drug eluting implants. Additionally, microfabricated vaccine delivery systems are presented due to the great impact they can have in obtaining a cold chain-free vaccine, with long-term stability. Microfabrication will continue to offer new, alternative solutions for the development of smart, advanced drug delivery systems. PMID:28773770

Utilization of Selected Data Mining Methods for Communication Network Analysis

Directory of Open Access Journals (Sweden)

V. Ondryhal

2011-06-01

Full Text Available The aim of the project was to analyze the behavior of military communication networks based on work with real data collected continuously since 2005. With regard to the nature and amount of the data, data mining methods were selected for the purpose of analyses and experiments. The quality of real data is often insufficient for an immediate analysis. The article presents the data cleaning operations which have been carried out with the aim to improve the input data sample to obtain reliable models. Gradually, by means of properly chosen SW, network models were developed to verify generally valid patterns of network behavior as a bulk service. Furthermore, unlike the commercially available communication networks simulators, the models designed allowed us to capture nonstandard models of network behavior under an increased load, verify the correct sizing of the network to the increased load, and thus test its reliability. Finally, based on previous experience, the models enabled us to predict emergency situations with a reasonable accuracy.

A study of reactor monitoring method with neural network

Energy Technology Data Exchange (ETDEWEB)

Nabeshima, Kunihiko [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment

2001-03-01

The purpose of this study is to investigate the methodology of Nuclear Power Plant (NPP) monitoring with neural networks, which create the plant models by the learning of the past normal operation patterns. The concept of this method is to detect the symptom of small anomalies by monitoring the deviations between the process signals measured from an actual plant and corresponding output signals from the neural network model, which might not be equal if the abnormal operational patterns are presented to the input of the neural network. Auto-associative network, which has same output as inputs, can detect an kind of anomaly condition by using normal operation data only. The monitoring tests of the feedforward neural network with adaptive learning were performed using the PWR plant simulator by which many kinds of anomaly conditions can be easily simulated. The adaptively trained feedforward network could follow the actual plant dynamics and the changes of plant condition, and then find most of the anomalies much earlier than the conventional alarm system during steady state and transient operations. Then the off-line and on-line test results during one year operation at the actual NPP (PWR) showed that the neural network could detect several small anomalies which the operators or the conventional alarm system didn't noticed. Furthermore, the sensitivity analysis suggests that the plant models by neural networks are appropriate. Finally, the simulation results show that the recurrent neural network with feedback connections could successfully model the slow behavior of the reactor dynamics without adaptive learning. Therefore, the recurrent neural network with adaptive learning will be the best choice for the actual reactor monitoring system. (author)

An effective method to improve the robustness of small-world networks under attack

International Nuclear Information System (INIS)

Zhang Zheng-Zhen; Xu Wen-Jun; Lin Jia-Ru; Zeng Shang-You

2014-01-01

In this study, the robustness of small-world networks to three types of attack is investigated. Global efficiency is introduced as the network coefficient to measure the robustness of a small-world network. The simulation results prove that an increase in rewiring probability or average degree can enhance the robustness of the small-world network under all three types of attack. The effectiveness of simultaneously increasing both rewiring probability and average degree is also studied, and the combined increase is found to significantly improve the robustness of the small-world network. Furthermore, the combined effect of rewiring probability and average degree on network robustness is shown to be several times greater than that of rewiring probability or average degree individually. This means that small-world networks with a relatively high rewiring probability and average degree have advantages both in network communications and in good robustness to attacks. Therefore, simultaneously increasing rewiring probability and average degree is an effective method of constructing realistic networks. Consequently, the proposed method is useful to construct efficient and robust networks in a realistic scenario. (interdisciplinary physics and related areas of science and technology)

Drug delivery device including electrolytic pump

KAUST Repository

Foulds, Ian G.; Buttner, Ulrich; Yi, Ying

2016-01-01

Systems and methods are provided for a drug delivery device and use of the device for drug delivery. In various aspects, the drug delivery device combines a “solid drug in reservoir” (SDR) system with an electrolytic pump. In various aspects an improved electrolytic pump is provided including, in particular, an improved electrolytic pump for use with a drug delivery device, for example an implantable drug delivery device. A catalytic reformer can be incorporated in a periodically pulsed electrolytic pump to provide stable pumping performance and reduced actuation cycle.

Drug delivery device including electrolytic pump

KAUST Repository

Foulds, Ian G.

2016-03-31

Systems and methods are provided for a drug delivery device and use of the device for drug delivery. In various aspects, the drug delivery device combines a “solid drug in reservoir” (SDR) system with an electrolytic pump. In various aspects an improved electrolytic pump is provided including, in particular, an improved electrolytic pump for use with a drug delivery device, for example an implantable drug delivery device. A catalytic reformer can be incorporated in a periodically pulsed electrolytic pump to provide stable pumping performance and reduced actuation cycle.

Enriching the tactical network design of express service carriers with fleet scheduling characteristics

NARCIS (Netherlands)

Meuffels, W.J.M.; Fleuren, H.A.; Cruijssen, F.C.A.M.; Dam, E.R.

2010-01-01

Express service carriers provide time-guaranteed deliveries of parcels via a network consisting of nodes and hubs. In this, nodes take care of the collection and delivery of parcels, and hubs have the function to consolidate parcels in between the nodes. The tactical network design problem assigns

Applications of polymeric nanocapsules in field of drug delivery systems.

Science.gov (United States)

Rong, Xinyu; Xie, Yinghua; Hao, Xiaomei; Chen, Tao; Wang, Yingming; Liu, Yuanyuan

2011-09-01

Drug-loaded polymeric nanocapsules have exhibited potential applications in the field of drug delivery systems in recent years. This article entails the biodegradable polymers generally used for preparing nanocapsules, which include both natural polymers and synthetic polymers. Furthermore, the article presents a general review of the different preparation methods: nanoprecipitation method, emulsion-diffusion method, double emulsification method, emulsion-coacervation method, layer-by-layer assembly method. In addition, the analysis methods of nanocapsule characteristics, such as mean size, morphology, surface characteristics, shell thickness, encapsulation efficiency, active substance release, dispersion stability, are mentioned. Also, the applications of nanocapsules as carriers for use in drug delivery systems are reviewed, which primarily involve targeting drug delivery, controlled/sustained release drug delivery systems, transdermal drug delivery systems and improving stability and bioavailability of drugs. Nanocapsules, prepared with different biodegradable polymers, have received more and more attention and have been regarded as one of the most promising drug delivery systems.

Comparative Analysis of Neural Network Training Methods in Real-time Radiotherapy

Directory of Open Access Journals (Sweden)

Nouri S.

2017-03-01

Full Text Available Background: The motions of body and tumor in some regions such as chest during radiotherapy treatments are one of the major concerns protecting normal tissues against high doses. By using real-time radiotherapy technique, it is possible to increase the accuracy of delivered dose to the tumor region by means of tracing markers on the body of patients. Objective: This study evaluates the accuracy of some artificial intelligence methods including neural network and those of combination with genetic algorithm as well as particle swarm optimization (PSO estimating tumor positions in real-time radiotherapy. Method: One hundred recorded signals of three external markers were used as input data. The signals from 3 markers thorough 10 breathing cycles of a patient treated via a cyber-knife for a lung tumor were used as data input. Then, neural network method and its combination with genetic or PSO algorithms were applied determining the tumor locations using MATLAB© software program. Results: The accuracies were obtained 0.8%, 12% and 14% in neural network, genetic and particle swarm optimization algorithms, respectively. Conclusion: The internal target volume (ITV should be determined based on the applied neural network algorithm on training steps.

An inter-centre quality assurance network for IMRT verification: Results of the ESTRO QUASIMODO project

International Nuclear Information System (INIS)

Gillis, Sofie; Wagter, Carlos de; Bohsung, Joerg; Perrin, Bruce; Williams, Peter; Mijnheer, Ben J.

2005-01-01

Background and purpose: IMRT necessitates extension of existing inter-centre quality assurance programs due to its increased complexity. We assessed the feasibility of an inter-centre verification method for different IMRT techniques. Materials and methods: Eight European radiotherapy institutions of the QUASIMODO network, have designed an IMRT plan for a horseshoe-shaped PTV surrounding a cylindrical OAR in a simplified pelvic phantom. All centres applied common plan objectives but used their own equipment for planning and delivery. They verified the delivery of this plan according to a common protocol with radiographic film and ionisation chamber measurements. The irradiated films, the results of the ionisation chamber measurements and the computed dose distributions were sent to one analysis centre that compared the measured and computed dose distributions with the gamma method and composite dose-area histograms. Results: 4% (relative to the prescribed dose) and 3 mm (distance-to-agreement) were decided feasible gamma criteria. The composite dose-area histograms showed a maximum local deviation of 3.5% in the mean dose of the PTV and 5% in the OAR. Systematic differences could be identified, and in some cases explained. Conclusions: This multi-centre dosimetric verification study demonstrated both the feasibility of a multi-centre quality assurance network to evaluate any IMRT planning and delivery system combination, as well as the validity of the methodology involved

A BHR Composite Network-Based Visualization Method for Deformation Risk Level of Underground Space.

Directory of Open Access Journals (Sweden)

Wei Zheng

Full Text Available This study proposes a visualization processing method for the deformation risk level of underground space. The proposed method is based on a BP-Hopfield-RGB (BHR composite network. Complex environmental factors are integrated in the BP neural network. Dynamic monitoring data are then automatically classified in the Hopfield network. The deformation risk level is combined with the RGB color space model and is displayed visually in real time, after which experiments are conducted with the use of an ultrasonic omnidirectional sensor device for structural deformation monitoring. The proposed method is also compared with some typical methods using a benchmark dataset. Results show that the BHR composite network visualizes the deformation monitoring process in real time and can dynamically indicate dangerous zones.

First-order design of geodetic networks using the simulated annealing method

Science.gov (United States)

Berné, J. L.; Baselga, S.

2004-09-01

The general problem of the optimal design for a geodetic network subject to any extrinsic factors, namely the first-order design problem, can be dealt with as a numeric optimization problem. The classic theory of this problem and the optimization methods are revised. Then the innovative use of the simulated annealing method, which has been successfully applied in other fields, is presented for this classical geodetic problem. This method, belonging to iterative heuristic techniques in operational research, uses a thermodynamical analogy to crystalline networks to offer a solution that converges probabilistically to the global optimum. Basic formulation and some examples are studied.

Modulation of electrostatic interactions to improve controlled drug delivery from nanogels.

Science.gov (United States)

Mauri, Emanuele; Chincarini, Giulia M F; Rigamonti, Riccardo; Magagnin, Luca; Sacchetti, Alessandro; Rossi, Filippo

2017-03-01

The synthesis of nanogels as devices capable to maintain the drug level within a desired range for a long and sustained period of time is a leading strategy in controlled drug delivery. However, with respect to the good results obtained with antibodies and peptides there are a lot of problems related to the quick and uncontrolled diffusion of small hydrophilic molecules through polymeric network pores. For these reasons research community is pointing toward the use of click strategies to reduce release rates of the linked drugs to the polymer chains. Here we propose an alternative method that considers the electrostatic interactions between polymeric chains and drugs to tune the release kinetics from nanogel network. The main advantage of these systems lies in the fact that the carried drugs are not modified and no chemical reactions take place during their loading and release. In this work we synthesized PEG-PEI based nanogels with different protonation degrees and the release kinetics with charged and uncharged drug mimetics (sodium fluorescein, SF, and rhodamine B, RhB) were studied. Moreover, also the effect of counterion used to induce protonation was taken into account in order to build a tunable drug delivery system able to provide multiple release rates with the same device. Copyright © 2016 Elsevier B.V. All rights reserved.

A Biologically Inspired Energy-Efficient Duty Cycle Design Method for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jie Zhou

2017-01-01

Full Text Available The recent success of emerging wireless sensor networks technology has encouraged researchers to develop new energy-efficient duty cycle design algorithm in this field. The energy-efficient duty cycle design problem is a typical NP-hard combinatorial optimization problem. In this paper, we investigate an improved elite immune evolutionary algorithm (IEIEA strategy to optimize energy-efficient duty cycle design scheme and monitored area jointly to enhance the network lifetimes. Simulation results show that the network lifetime of the proposed IEIEA method increased compared to the other two methods, which means that the proposed method improves the full coverage constraints.

WMAXC: a weighted maximum clique method for identifying condition-specific sub-network.

Directory of Open Access Journals (Sweden)

Bayarbaatar Amgalan

Full Text Available Sub-networks can expose complex patterns in an entire bio-molecular network by extracting interactions that depend on temporal or condition-specific contexts. When genes interact with each other during cellular processes, they may form differential co-expression patterns with other genes across different cell states. The identification of condition-specific sub-networks is of great importance in investigating how a living cell adapts to environmental changes. In this work, we propose the weighted MAXimum clique (WMAXC method to identify a condition-specific sub-network. WMAXC first proposes scoring functions that jointly measure condition-specific changes to both individual genes and gene-gene co-expressions. It then employs a weaker formula of a general maximum clique problem and relates the maximum scored clique of a weighted graph to the optimization of a quadratic objective function under sparsity constraints. We combine a continuous genetic algorithm and a projection procedure to obtain a single optimal sub-network that maximizes the objective function (scoring function over the standard simplex (sparsity constraints. We applied the WMAXC method to both simulated data and real data sets of ovarian and prostate cancer. Compared with previous methods, WMAXC selected a large fraction of cancer-related genes, which were enriched in cancer-related pathways. The results demonstrated that our method efficiently captured a subset of genes relevant under the investigated condition.

Towards Scalable and Interactive Delivery of Immersive Media.

NARCIS (Netherlands)

Niamut, O.A.; Macq, J.F.; Prins, M.J.; Brandenburg, R. van; Verzijp, N.; Alface, P.R.

2012-01-01

Within the EU FP7 project FascinatE, a capture, production and delivery system capable of allowing end-users to interactively view and navigate around an ultra-high resolution video panorama showing a live event is being developed. Within this system, network-based processing is used to repurpose

Justification of the project a network of freight terminals unitized cargo

Directory of Open Access Journals (Sweden)

Ilesaliev D.I.

2016-12-01

Full Text Available In this paper we consider the question of Uzbekistan in promoting the development of international transport in supply chains. The development of transport infrastructure to ensure timely delivery of goods is one of the main tasks in supply chain management. The aim is to study of the project network terminal unitized cargo Uzbekistan in supply chains. Methods the study is based on analysis of existing methods and techniques of Russian scientists in the field of place-ment of objects. The method of searching the most rational location of logistics facility in the supply chain. Also pre-justified the project network terminal unitized cargo in Uzbekistan. Given the state of the problems and prospects of transport logistics of Uzbekistan, the developed method can be used by experts when performing the supporting calcula-tions location of logistic objects.

View-invariant gait recognition method by three-dimensional convolutional neural network

Science.gov (United States)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Least-squares methods for identifying biochemical regulatory networks from noisy measurements

Directory of Open Access Journals (Sweden)

Heslop-Harrison Pat

2007-01-01

Full Text Available Abstract Background We consider the problem of identifying the dynamic interactions in biochemical networks from noisy experimental data. Typically, approaches for solving this problem make use of an estimation algorithm such as the well-known linear Least-Squares (LS estimation technique. We demonstrate that when time-series measurements are corrupted by white noise and/or drift noise, more accurate and reliable identification of network interactions can be achieved by employing an estimation algorithm known as Constrained Total Least Squares (CTLS. The Total Least Squares (TLS technique is a generalised least squares method to solve an overdetermined set of equations whose coefficients are noisy. The CTLS is a natural extension of TLS to the case where the noise components of the coefficients are correlated, as is usually the case with time-series measurements of concentrations and expression profiles in gene networks. Results The superior performance of the CTLS method in identifying network interactions is demonstrated on three examples: a genetic network containing four genes, a network describing p53 activity and mdm2 messenger RNA interactions, and a recently proposed kinetic model for interleukin (IL-6 and (IL-12b messenger RNA expression as a function of ATF3 and NF-κB promoter binding. For the first example, the CTLS significantly reduces the errors in the estimation of the Jacobian for the gene network. For the second, the CTLS reduces the errors from the measurements that are corrupted by white noise and the effect of neglected kinetics. For the third, it allows the correct identification, from noisy data, of the negative regulation of (IL-6 and (IL-12b by ATF3. Conclusion The significant improvements in performance demonstrated by the CTLS method under the wide range of conditions tested here, including different levels and types of measurement noise and different numbers of data points, suggests that its application will enable

State-of-the-art of home networking

NARCIS (Netherlands)

Koonen, A.M.J.; Popov, M.

2012-01-01

To introduce the Symposium on "Indoor Optical Networks: a Promising Way to a Converged Service Delivery", this presentation will give a brief overview of state-of-the-art home networking architectures, technologies and applications covering both technical and techno-economic aspects.

Method of targeted delivery of laser beam to isolated retinal rods by fiber optics.

Science.gov (United States)

Sim, Nigel; Bessarab, Dmitri; Jones, C Michael; Krivitsky, Leonid

2011-11-01

A method of controllable light delivery to retinal rod cells using an optical fiber is described. Photo-induced current of the living rod cells was measured with the suction electrode technique. The approach was tested with measurements relating the spatial distribution of the light intensity to photo-induced current. In addition, the ion current responses of rod cells to polarized light at two different orientation geometries of the cells were studied.

Communication Network Analysis Methods.

Science.gov (United States)

Farace, Richard V.; Mabee, Timothy

This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…

A method of reconstructing the spatial measurement network by mobile measurement transmitter for shipbuilding

International Nuclear Information System (INIS)

Guo, Siyang; Lin, Jiarui; Yang, Linghui; Ren, Yongjie; Guo, Yin

2017-01-01

The workshop Measurement Position System (wMPS) is a distributed measurement system which is suitable for the large-scale metrology. However, there are some inevitable measurement problems in the shipbuilding industry, such as the restriction by obstacles and limited measurement range. To deal with these factors, this paper presents a method of reconstructing the spatial measurement network by mobile transmitter. A high-precision coordinate control network with more than six target points is established. The mobile measuring transmitter can be added into the measurement network using this coordinate control network with the spatial resection method. This method reconstructs the measurement network and broadens the measurement scope efficiently. To verify this method, two comparison experiments are designed with the laser tracker as the reference. The results demonstrate that the accuracy of point-to-point length is better than 0.4mm and the accuracy of coordinate measurement is better than 0.6mm. (paper)

A Newly Developed Method for Computing Reliability Measures in a Water Supply Network

Directory of Open Access Journals (Sweden)

Jacek Malinowski

2016-01-01

Full Text Available A reliability model of a water supply network has beens examined. Its main features are: a topology that can be decomposed by the so-called state factorization into a (relativelysmall number of derivative networks, each having a series-parallel structure (1, binary-state components (either operative or failed with given flow capacities (2, a multi-state character of the whole network and its sub-networks - a network state is defined as the maximal flow between a source (sources and a sink (sinks (3, all capacities (component, network, and sub-network have integer values (4. As the network operates, its state changes due to component failures, repairs, and replacements. A newly developed method of computing the inter-state transition intensities has been presented. It is based on the so-called state factorization and series-parallel aggregation. The analysis of these intensities shows that the failure-repair process of the considered system is an asymptotically homogenous Markov process. It is also demonstrated how certain reliability parameters useful for the network maintenance planning can be determined on the basis of the asymptotic intensities. For better understanding of the presented method, an illustrative example is given. (original abstract

Vector-free intracellular delivery by reversible permeabilization.

Directory of Open Access Journals (Sweden)

Shirley O'Dea

Full Text Available Despite advances in intracellular delivery technologies, efficient methods are still required that are vector-free, can address a wide range of cargo types and can be applied to cells that are difficult to transfect whilst maintaining cell viability. We have developed a novel vector-free method that uses reversible permeabilization to achieve rapid intracellular delivery of cargos with varying composition, properties and size. A permeabilizing delivery solution was developed that contains a low level of ethanol as the permeabilizing agent. Reversal of cell permeabilization is achieved by temporally and volumetrically controlling the contact of the target cells with this solution. Cells are seeded in conventional multi-well plates. Following removal of the supernatant, the cargo is mixed with the delivery solution and applied directly to the cells using an atomizer. After a short incubation period, permeabilization is halted by incubating the cells in a phosphate buffer saline solution that dilutes the ethanol and is non-toxic to the permeabilized cells. Normal culture medium is then added. The procedure lasts less than 5 min. With this method, proteins, mRNA, plasmid DNA and other molecules have been delivered to a variety of cell types, including primary cells, with low toxicity and cargo functionality has been confirmed in proof-of-principle studies. Co-delivery of different cargo types has also been demonstrated. Importantly, delivery occurs by diffusion directly into the cytoplasm in an endocytic-independent manner. Unlike some other vector-free methods, adherent cells are addressed in situ without the need for detachment from their substratum. The method has also been adapted to address suspension cells. This delivery method is gentle yet highly reproducible, compatible with high throughput and automated cell-based assays and has the potential to enable a broad range of research, drug discovery and clinical applications.

Fractional laser-assisted drug delivery

DEFF Research Database (Denmark)

Taudorf, Elisabeth Hjardem; Lerche, C.M.; Erlendsson, A M

2016-01-01

BACKGROUND AND OBJECTIVE: Ablative fractional laser (AFXL) facilitates delivery of topical methotrexate (MTX). This study investigates impact of laser-channel depth on topical MTX-delivery. MATERIALS AND METHODS: MTX (1% [w/v]) diffused for 21 hours through AFXL-exposed porcine skin in in vitro F...

Coordinator Role Mobility Method for Increasing the Life Expectancy of Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Jurenoks Aleksejs

2017-05-01

Full Text Available The general problem of wireless sensor network nodes is the low-power batteries that significantly limit the life expectancy of a network. Nowadays the technical solutions related to energy resource management are being rapidly developed and integrated into the daily lives of people. The energy resource management systems use sensor networks for receiving and processing information during the realia time. The present paper proposes using a coordinator role mobility method for controlling the routing processes for energy balancing in nodes, which provides dynamic network reconfiguration possibilities. The method is designed to operate fully in the background and can be integrated into any exiting working system.

Node-Dependence-Based Dynamic Incentive Algorithm in Opportunistic Networks

Directory of Open Access Journals (Sweden)

Ruiyun Yu

2014-01-01

Full Text Available Opportunistic networks lack end-to-end paths between source nodes and destination nodes, so the communications are mainly carried out by the “store-carry-forward” strategy. Selfish behaviors of rejecting packet relay requests will severely worsen the network performance. Incentive is an efficient way to reduce selfish behaviors and hence improves the reliability and robustness of the networks. In this paper, we propose the node-dependence-based dynamic gaming incentive (NDI algorithm, which exploits the dynamic repeated gaming to motivate nodes relaying packets for other nodes. The NDI algorithm presents a mechanism of tolerating selfish behaviors of nodes. Reward and punishment methods are also designed based on the node dependence degree. Simulation results show that the NDI algorithm is effective in increasing the delivery ratio and decreasing average latency when there are a lot of selfish nodes in the opportunistic networks.

Research on Large-Scale Road Network Partition and Route Search Method Combined with Traveler Preferences

Directory of Open Access Journals (Sweden)

De-Xin Yu

2013-01-01

Full Text Available Combined with improved Pallottino parallel algorithm, this paper proposes a large-scale route search method, which considers travelers’ route choice preferences. And urban road network is decomposed into multilayers effectively. Utilizing generalized travel time as road impedance function, the method builds a new multilayer and multitasking road network data storage structure with object-oriented class definition. Then, the proposed path search algorithm is verified by using the real road network of Guangzhou city as an example. By the sensitive experiments, we make a comparative analysis of the proposed path search method with the current advanced optimal path algorithms. The results demonstrate that the proposed method can increase the road network search efficiency by more than 16% under different search proportion requests, node numbers, and computing process numbers, respectively. Therefore, this method is a great breakthrough in the guidance field of urban road network.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks.

Science.gov (United States)

Yang, Liu; Lu, Yinzhi; Zhong, Yuanchang; Wu, Xuegang; Yang, Simon X

2015-12-26

Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs) because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC) algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs) in the network act as routers to transmit data to base station (BS) cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

A Multi-Hop Energy Neutral Clustering Algorithm for Maximizing Network Information Gathering in Energy Harvesting Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Liu Yang

2015-12-01

Full Text Available Energy resource limitation is a severe problem in traditional wireless sensor networks (WSNs because it restricts the lifetime of network. Recently, the emergence of energy harvesting techniques has brought with them the expectation to overcome this problem. In particular, it is possible for a sensor node with energy harvesting abilities to work perpetually in an Energy Neutral state. In this paper, a Multi-hop Energy Neutral Clustering (MENC algorithm is proposed to construct the optimal multi-hop clustering architecture in energy harvesting WSNs, with the goal of achieving perpetual network operation. All cluster heads (CHs in the network act as routers to transmit data to base station (BS cooperatively by a multi-hop communication method. In addition, by analyzing the energy consumption of intra- and inter-cluster data transmission, we give the energy neutrality constraints. Under these constraints, every sensor node can work in an energy neutral state, which in turn provides perpetual network operation. Furthermore, the minimum network data transmission cycle is mathematically derived using convex optimization techniques while the network information gathering is maximal. Simulation results show that our protocol can achieve perpetual network operation, so that the consistent data delivery is guaranteed. In addition, substantial improvements on the performance of network throughput are also achieved as compared to the famous traditional clustering protocol LEACH and recent energy harvesting aware clustering protocols.

Modified network simulation model with token method of bus access

Directory of Open Access Journals (Sweden)

L.V. Stribulevich

2013-08-01

Full Text Available Purpose. To study the characteristics of the local network with the marker method of access to the bus its modified simulation model was developed. Methodology. Defining characteristics of the network is carried out on the developed simulation model, which is based on the state diagram-layer network station with the mechanism of processing priorities, both in steady state and in the performance of control procedures: the initiation of a logical ring, the entrance and exit of the station network with a logical ring. Findings. A simulation model, on the basis of which can be obtained the dependencies of the application the maximum waiting time in the queue for different classes of access, and the reaction time usable bandwidth on the data rate, the number of network stations, the generation rate applications, the number of frames transmitted per token holding time, frame length was developed. Originality. The technique of network simulation reflecting its work in the steady condition and during the control procedures, the mechanism of priority ranking and handling was proposed. Practical value. Defining network characteristics in the real-time systems on railway transport based on the developed simulation model.

Family-centred care delivery

Science.gov (United States)

Mayo-Bruinsma, Liesha; Hogg, William; Taljaard, Monica; Dahrouge, Simone

2013-01-01

Abstract Objective To determine whether models of primary care service delivery differ in their provision of family-centred care (FCC) and to identify practice characteristics associated with FCC. Design Cross-sectional study. Setting Primary care practices in Ontario (ie, 35 salaried community health centres, 35 fee-for-service practices, 32 capitation-based health service organizations, and 35 blended remuneration family health networks) that belong to 4 models of primary care service delivery. Participants A total of 137 practices, 363 providers, and 5144 patients. Main outcome measures Measures of FCC in patient and provider surveys were based on the Primary Care Assessment Tool. Statistical analyses were conducted using linear mixed regression models and generalized estimating equations. Results Patient-reported FCC scores were high and did not vary significantly by primary care model. Larger panel size in a practice was associated with lower odds of patients reporting FCC. Provider-reported FCC scores were significantly higher in community health centres than in family health networks (P = .035). A larger number of nurse practitioners and clinical services on-site were both associated with higher FCC scores, while scores decreased as the number of family physicians in a practice increased and if practices were more rural. Conclusion Based on provider and patient reports, primary care reform strategies that encourage larger practices and more patients per family physician might compromise the provision of FCC, while strategies that encourage multidisciplinary practices and a range of services might increase FCC. PMID:24235195

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

Science.gov (United States)

Rash, James

2014-01-01

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial

Neural network CT image reconstruction method for small amount of projection data

International Nuclear Information System (INIS)

Ma, X.F.; Fukuhara, M.; Takeda, T.

2000-01-01

This paper presents a new method for two-dimensional image reconstruction by using a multi-layer neural network. Though a conventionally used object function of such a neural network is composed of a sum of squared errors of the output data, we define an object function composed of a sum of squared residuals of an integral equation. By employing an appropriate numerical line integral for this integral equation, we can construct a neural network which can be used for CT image reconstruction for cases with small amount of projection data. We applied this method to some model problems and obtained satisfactory results. This method is especially useful for analyses of laboratory experiments or field observations where only a small amount of projection data is available in comparison with the well-developed medical applications

Neural network CT image reconstruction method for small amount of projection data

CERN Document Server

Ma, X F; Takeda, T

2000-01-01

This paper presents a new method for two-dimensional image reconstruction by using a multi-layer neural network. Though a conventionally used object function of such a neural network is composed of a sum of squared errors of the output data, we define an object function composed of a sum of squared residuals of an integral equation. By employing an appropriate numerical line integral for this integral equation, we can construct a neural network which can be used for CT image reconstruction for cases with small amount of projection data. We applied this method to some model problems and obtained satisfactory results. This method is especially useful for analyses of laboratory experiments or field observations where only a small amount of projection data is available in comparison with the well-developed medical applications.

Selection of variables for neural network analysis. Comparisons of several methods with high energy physics data

International Nuclear Information System (INIS)

Proriol, J.

1994-01-01

Five different methods are compared for selecting the most important variables with a view to classifying high energy physics events with neural networks. The different methods are: the F-test, Principal Component Analysis (PCA), a decision tree method: CART, weight evaluation, and Optimal Cell Damage (OCD). The neural networks use the variables selected with the different methods. We compare the percentages of events properly classified by each neural network. The learning set and the test set are the same for all the neural networks. (author)

A novel Bayesian learning method for information aggregation in modular neural networks

DEFF Research Database (Denmark)

Wang, Pan; Xu, Lida; Zhou, Shang-Ming

2010-01-01

Modular neural network is a popular neural network model which has many successful applications. In this paper, a sequential Bayesian learning (SBL) is proposed for modular neural networks aiming at efficiently aggregating the outputs of members of the ensemble. The experimental results on eight...... benchmark problems have demonstrated that the proposed method can perform information aggregation efficiently in data modeling....

Traffic Management by Using Admission Control Methods in Multiple Node IMS Network

Directory of Open Access Journals (Sweden)

Filip Chamraz

2016-01-01

Full Text Available The paper deals with Admission Control methods (AC as a possible solution for traffic management in IMS networks (IP Multimedia Subsystem - from the point of view of an efficient redistribution of the available network resources and keeping the parameters of Quality of Service (QoS. The paper specifically aims at the selection of the most appropriate method for the specific type of traffic and traffic management concept using AC methods on multiple nodes. The potential benefit and disadvantage of the used solution is evaluated.

Professional social networking.

Science.gov (United States)

Rowley, Robert D

2014-12-01

We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

A Glider-Assisted Link Disruption Restoration Mechanism in Underwater Acoustic Sensor Networks.

Science.gov (United States)

Jin, Zhigang; Wang, Ning; Su, Yishan; Yang, Qiuling

2018-02-07

Underwater acoustic sensor networks (UASNs) have become a hot research topic. In UASNs, nodes can be affected by ocean currents and external forces, which could result in sudden link disruption. Therefore, designing a flexible and efficient link disruption restoration mechanism to ensure the network connectivity is a challenge. In the paper, we propose a glider-assisted restoration mechanism which includes link disruption recognition and related link restoring mechanism. In the link disruption recognition mechanism, the cluster heads collect the link disruption information and then schedule gliders acting as relay nodes to restore the disrupted link. Considering the glider's sawtooth motion, we design a relay location optimization algorithm with a consideration of both the glider's trajectory and acoustic channel attenuation model. The utility function is established by minimizing the channel attenuation and the optimal location of glider is solved by a multiplier method. The glider-assisted restoration mechanism can greatly improve the packet delivery rate and reduce the communication energy consumption and it is more general for the restoration of different link disruption scenarios. The simulation results show that glider-assisted restoration mechanism can improve the delivery rate of data packets by 15-33% compared with cooperative opportunistic routing (OVAR), the hop-by-hop vector-based forwarding (HH-VBF) and the vector based forward (VBF) methods, and reduce communication energy consumption by 20-58% for a typical network's setting.

Family-centred care delivery: comparing models of primary care service delivery in Ontario.

Science.gov (United States)

Mayo-Bruinsma, Liesha; Hogg, William; Taljaard, Monica; Dahrouge, Simone

2013-11-01

To determine whether models of primary care service delivery differ in their provision of family-centred care (FCC) and to identify practice characteristics associated with FCC. Cross-sectional study. Primary care practices in Ontario (ie, 35 salaried community health centres, 35 fee-for-service practices, 32 capitation-based health service organizations, and 35 blended remuneration family health networks) that belong to 4 models of primary care service delivery. A total of 137 practices, 363 providers, and 5144 patients. Measures of FCC in patient and provider surveys were based on the Primary Care Assessment Tool. Statistical analyses were conducted using linear mixed regression models and generalized estimating equations. Patient-reported FCC scores were high and did not vary significantly by primary care model. Larger panel size in a practice was associated with lower odds of patients reporting FCC. Provider-reported FCC scores were significantly higher in community health centres than in family health networks (P = .035). A larger number of nurse practitioners and clinical services on-site were both associated with higher FCC scores, while scores decreased as the number of family physicians in a practice increased and if practices were more rural. Based on provider and patient reports, primary care reform strategies that encourage larger practices and more patients per family physician might compromise the provision of FCC, while strategies that encourage multidisciplinary practices and a range of services might increase FCC.

A perspective from Europe on in-home networking

NARCIS (Netherlands)

Koonen, A.M.J.; Shi, Y.; Tran, N.C.; Okonkwo, C.M.; Boom, van den H.P.A.; Tangdiongga, E.

2012-01-01

Delivery of wirebound and wireless services can be integrated in a single cost-efficient in-home POF network, when using advanced signal modulation techniques. In larger buildings, dynamic capacity allocation by wavelength routing improves the network performance.

Laser beam uniformity and stability using homogenizer-based fiber optic launch method: square core fiber delivery

Science.gov (United States)

Lizotte, Todd E.

2011-03-01

Over the years, technological achievements within the laser medical diagnostic, treatment, and therapy markets have led to ever increasing requirements for greater control of critical laser beam parameters. Increased laser power/energy stabilization, temporal and spatial beam shaping and flexible laser beam delivery systems with ergonomic focusing or imaging lens systems are sought by leading medical laser system producers. With medical procedures that utilize laser energy, there is a constant emphasis on reducing adverse effects that come about by the laser itself or its optical system, but even when these variables are well controlled the medical professional will still need to deal with the multivariate nature of the human body. Focusing on the variables that can be controlled, such as accurate placement of the laser beam where it will expose a surface being treated as well as laser beam shape and uniformity is critical to minimizing adverse conditions. This paper covers the use of fiber optic beam delivery as a means of defining the beam shape (intensity/power distribution uniformity) at the target plane as well as the use of fiber delivery as a means to allow more flexible articulation of the laser beam over the surface being treated. The paper will present a new concept of using a square core fiber beam delivery design utilizing a unique micro lens array (MLA) launch method that improves the overall stability of the system, by minimizing the impact of the laser instability. The resulting performance of the prototype is presented to demonstrate its stability in comparison to simple lens launch techniques, with an emphasis on homogenization and articulated fiber delivery.

A method for under-sampled ecological network data analysis: plant-pollination as case study

Directory of Open Access Journals (Sweden)

Peter B. Sorensen

2012-01-01

Full Text Available In this paper, we develop a method, termed the Interaction Distribution (ID method, for analysis of quantitative ecological network data. In many cases, quantitative network data sets are under-sampled, i.e. many interactions are poorly sampled or remain unobserved. Hence, the output of statistical analyses may fail to differentiate between patterns that are statistical artefacts and those which are real characteristics of ecological networks. The ID method can support assessment and inference of under-sampled ecological network data. In the current paper, we illustrate and discuss the ID method based on the properties of plant-animal pollination data sets of flower visitation frequencies. However, the ID method may be applied to other types of ecological networks. The method can supplement existing network analyses based on two definitions of the underlying probabilities for each combination of pollinator and plant species: (1, pi,j: the probability for a visit made by the i’th pollinator species to take place on the j’th plant species; (2, qi,j: the probability for a visit received by the j’th plant species to be made by the i’th pollinator. The method applies the Dirichlet distribution to estimate these two probabilities, based on a given empirical data set. The estimated mean values for pi,j and qi,j reflect the relative differences between recorded numbers of visits for different pollinator and plant species, and the estimated uncertainty of pi,j and qi,j decreases with higher numbers of recorded visits.