DDAVP use during pregnancy: an analysis of its safety for mother and child

Synthetic 1-deamino-8-D-arginine-vasopressin (DDAVP) is used in the management of diabetes insipidus (DI). We conducted a systematic literature review of DDAVP use during pregnancy, with particular attention to its safety for both mother and infant. Studies were identified through Ovid MEDLINE from 1976 to July 1997 using the combined terms "desmopressin," "DDAVP," and "pregnancy". Review articles and published letters were also explored. One hundred one articles were retrieved, of which 20 met all the inclusion criteria. Included in the 20 articles were 53 cases with the use of DDAVP for the management of DI. The therapeutic daily dose of DDAVP was approximately 29 micrograms intranasally (range 7.5-100 micrograms), with adequate DI control observed. Three of 14 women with sufficient information developed preeclampsia, a nonsignificant difference from the expected rate of 5 percent (the Fisher exact test, 2-P = .08). The mode of delivery was defined for 22 cases, with 16 uneventful vaginal births, and six cesarean delivery. There was no evidence of a drug interaction among the five women who received both DDAVP and intravenous oxytocin. Information was available on 49 live births born to DI mothers on DDAVP. The mean gestational age at delivery was 37.4 weeks (SD 1.3 weeks), with an estimated mean birth weight of 2963.8 gm (range 2000-4420 gm). Forty-three offspring were reported as healthy (event rate 87.8 percent; 95 percent CI 77.2-95.3 percent). Of the remaining six infants, one developed DI at 18 months of age; a second was under 2500 gm at birth, but survived; the third developed hypotonia and failure to thrive at 21 months, two others had Down syndrome; and the sixth died of severe cardiac anomalies. Similar data were seen among the 41 infants whose mothers had used DDAVP throughout pregnancy. In conclusion, DDAVP use during pregnancy seems to be safe for both mother and child. Delivery does not seem to be augmented by its use, nor are there likely any associated adverse neonatal effects. A large database of DDAVP use during pregnancy is needed to confirm these findings.     

User sensitive research in e-learning: exploring the role of individual user characteristics

The increasing need for active and accessible learning in the inclusive knowledge society drives the demand for e-learning that engages users much more effectively than ever before. In this context, it is crucial to conduct research that embraces innovation in user sensitive design, or else influential individual user differences may be overlooked. The objective of this paper is to explore the creation of successful e-learning systems that are able to increase users’ learning performance and enhance their personal learning experiences. The paper reports two converging and complimentary approaches, namely case studies and experimentation. First, case studies are used to explore the extent to which effective e-learning systems comply with eight specific factors. Of the eight, accessibility, individual differences and student modeling turn out to be the weakest points in current practice. Second, an empirical study investigates the influences of user individual user differences on users’ learning outcomes in an e-learning environment. The experiment found that individual differences in motivation to learn and expectations about e-learning significantly impacted users’ learning achievements. Third, based on these studies, improvements in research methodology are identified towards greater consideration of user sensitive research issues, thus enabling us to outline improved experimental procedures. Further experiment results should provide us with better insights into the arguments needed to carefully assess benefits of developing and involving a user model in an e-learning application. Consequently, evaluation and justification could now encompass both system performance as well as user performance.     

C-PSA: Constrained Pareto simulated annealing for constrained multi-objective optimization

In recent years, evolutionary algorithms (EAs) have been extensively developed and utilized to solve multi-objective optimization problems. However, some previous studies have shown that for certain problems, an approach which allows for non-greedy or uphill moves (unlike EAs), can be more beneficial. One such approach is simulated annealing (SA). SA is a proven heuristic for solving numerical optimization problems. But owing to its point-to-point nature of search, limited efforts has been made to explore its potential for solving multi-objective problems. The focus of the presented work is to develop a simulated annealing algorithm for constrained multi-objective problems. The performance of the proposed algorithm is reported on a number of difficult constrained benchmark problems. A comparison with other established multi-objective optimization algorithms, such as infeasibility driven evolutionary algorithm (IDEA), Non-dominated sorting genetic algorithm II (NSGA-II) and multi-objective Scatter search II (MOSS-II) has been included to highlight the benefits of the proposed approach.     

Feature-based statistical analysis of combustion simulation data

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing and reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion science; however, it is applicable to many other science domains.     

Using honeynodes for defense against jamming attacks in wireless infrastructure-based networks

The advent of wireless networks has brought a new set of security issues with it. One of the most feared of these is the jamming-based attacks. In this paper, we propose a pre-emptive detection strategy using honeynodes and a response mechanism based on the existing Channel Surfing Algorithm [Xu W, Trappe W, Zhang Y, Wood T. Channel surfing and spatial retreats: defenses against wireless denial of service. ACM Wireless Security 2004;80-9] to protect wireless nodes from a jammer. Honeynodes generate dummy communication at a frequency close to the actual frequency of operation, and pre-emptively alert authentic nodes of imminent attacks, so that the authentic nodes can jump to another frequency even before a jammer starts scanning that frequency. The next frequency is selected using a novel approach which uses a hybrid of reactive and proactive channel selection procedures. We have simulated the proposed approach using NS-2. The experimental results further prove a marked improvement in the performance of the proposed system over the Channel Surfing Algorithm in terms of the packet delivery ratio, the jammed duration, control message overhead and the number of channel re-configurations.     

An ant swarm-inspired energy-aware routing protocol for wireless ad-hoc networks

Primitive routing protocols for ad-hoc networks are “power hungry” and can therefore consume considerable amount of the limited amount of battery power resident in the nodes. Thus, routing in ad-hoc networks is very much energy-constrained. Continuous drainage of energy degrades battery performance as well. If a battery is allowed to intermittently remain in an idle state, it recovers some of its lost charge due to the charge recovery effect, which, in turn, results in prolonged battery life.In this paper, we use the ideas of naturally occurring ants’ foraging behavior (Dorigo and Stuetzle, 2004) [1] and based on those ideas, we design an energy-aware routing protocol, which not only incorporates the effect of power consumption in routing a packet, but also exploits the multi-path transmission properties of ant swarms and, hence, increases the battery life of a node. The efficiency of the protocol with respect to some of the existing ones has been established through simulations. It has been observed that the energy consumed in the network, the energy per packet in the case of EAAR are 60% less compared to MMBCR and the packets lost is only around 12% of what we have in AODV, in mobility scenarios.     

Supplier behavior modeling and winner determination using parallel MDP

Behavioral uncertainty of a supplier is a major challenge to a buyer operating in e-procurement setting. Modeling suppliers’ behavior from past transactions, estimation of possible future performance and integrating this knowledge with the winner determination process can bring a new dimension to procurement process automation. We propose a states-space model to capture the uncertainty involved in long-term supplier behavior. The states represent the performance level of a supplier. This behavioral aspect is then integrated with the winner determination process of a multi-attribute reverse auction for efficient supplier selection using parallel MDP. We also propose an implementation framework to collect the feedback on supplier, generate an aggregate performance score and integrate it with the winner determination process. The performance aggregation and winner determination with help of Markov decision process effectively uses the past performance information. In addition, it updates performance information in regular invervals and allevates the problem of maintaining a long history. We compare the MDP-based selection with that of performance score-based selection through a simulation experiment. It is observed that our scheme gives better buyer utility, selects best suppliers and fetches better quality product. The benefits realized through these attributes to the buyer increases the efficiency of the MDP-based selection process.     

Connectivity preserving localized coverage algorithm for area monitoring using wireless sensor networks

Efficient network coverage and connectivity are the requisites for most Wireless Sensor Network (WSN) deployments, particularly those concerned with area monitoring. Due to the resource constraints of the sensor nodes, redundancy of coverage area must be reduced for effective utilization of the available resources. If two nodes have the same coverage area in their active state, and if both the nodes are activated simultaneously, it leads to redundancy in network and wastage of precious sensor resources. In this paper, we address the problem of network coverage and connectivity and propose an efficient solution to maintain coverage, while preserving the connectivity of the network. The proposed solution aims to cover the area of interest (AOI), while minimizing the count of the active sensor nodes. The overlap region of two sensor nodes varies with the distance between the nodes. If the distance between two sensor nodes is maximized, the overall coverage area of these nodes will also be maximized. Also, to preserve the connectivity of the network, each sensor node must be in the communication range of at least one other node. Results of simulation of the proposed solution indicate up to 95% coverage of the area, while consuming very less energy of 9.44 J per unit time in the network, simulated in an area of 2500 m².     

Registration techniques for using imperfect and partially calibrated devices in planar multi-projector displays

Multi-projector displays today are automatically registered, both geometrically and photometrically, using cameras. Existing registration techniques assume pre-calibrated projectors and cameras that are devoid of imperfections such as lens distortion. In practice, however, these devices are usually imperfect and uncalibrated. Registration of each of these devices is often more challenging than the multi-projector display registration itself. To make tiled projection-based displays accessible to a layman user we should allow the use of uncalibrated inexpensive devices that are prone to imperfections. In this paper, we make two important advances in this direction. First, we present a new geometric registration technique that can achieve geometric alignment {\em in the presence of severe projector lens distortion} using a relatively inexpensive low-resolution camera. This is achieved via a closed-form model that relates the projectors to cameras, in planar multi-projector displays, using rational Bezier patches. This enables us to geometrically calibrate a 3000 x 2500 resolution planar multi-projector display made of 3 x 3 array of nine severely distorted projectors using a low resolution (640 x 480) VGA camera. Second, we present a photometric self-calibration technique for a projector-camera pair. This allows us to photometrically calibrate the same display made of nine projectors using a photometrically uncalibrated camera. To the best of our knowledge, this is the first work that allows geometrically imperfect projectors and photometrically uncalibrated cameras in calibrating multi-projector displays.