Factors associated with 2009 pandemic influenza A (H1N1) vaccination acceptance among university students from India during the post-pandemic phase

Background: There was a low adherence to influenza A (H1N1) vaccination program among university students and health care workers during the pandemic influenza in many parts of the world. Vaccination of high risk individuals is one of the recommendations of World Health Organization during the post-pandemic period. It is not documented about the student's knowledge, attitude and willingness to accept H1N1 vaccination during the post-pandemic period. We aimed to analyze the student's knowledge, attitude and willingness to accept H1N1 vaccination during the post-pandemic period in India. Methods: Vaccine against H1N1 was made available to the students of Vellore Institute of Technology, India from September 2010. The data are based on a cross-sectional study conducted during October 2010 to January 2011 using a self-administered questionnaire with a representative sample of the student population (N = 802). Results: Of the 802 respondents, only 102/802 (12.7%) had been vaccinated and 105/802 (13%) planned to do so in the future, while 595/802 (74%) would probably or definitely not get vaccinated in the future. The highest coverage was among the female (65/102, 63.7%) and non-compliance was higher among men in the group (384/595; 64.5%) (p < 0.0001). The representation of students from school of Bio-sciences and Bio-technology among vaccinees is significantly higher than that of other schools. Majority of the study population from the three groups perceived vaccine against H1N1 as the effective preventive measure when compared to other preventive measures. 250/595 (42%) of the responders argued of not being in the risk group. The risk perception was significantly higher among female (p < 0.0001). With in the study group, 453/802 (56.4%) said that they got the information, mostly from media. Conclusions: Our study shows that the vaccination coverage among university students remains very low in the post-pandemic period and doubts about the safety and effectiveness of the vaccine are key elements in their rejection. Our results indicate a need to provide accessible information about the vaccine safety by scientific authorities and fill gaps and confusions in this regard.

Synthesis of new (Bi, La)(3)MSb(2)O(11) phases (M = Cr, Mn, Fe) with KSbO(3)-type structure and their magnetic and photocatalytic properties

Synthesis and structure of new (Bi, La)(3)MSb(2)O(11) phases (M = Cr, Mn, Fe) are reported in conjunction with their magnetic and photocatalytic properties. XRD refinements reflect that Bi(3)CrSb(2)O(11), Bi(2)LaCrSb(2)O(11), Bi(2)LaMnSb(2)O(11) and Bi(2)LaFeSb(2)O(11) adopt KSbO(3)-type structure (space group, Pn (3) over bar). The structure can be described through three interpenetrating networks where the first is the (M/Sb)O(6) octahedral network and other two are the identical networks having Bi(6)O(4) composition. The magnetic measurements on Bi(2)LaCrSb(2)O(11) and Bi(2)LaMnSb(2)O(11) show paramagnetic behaviour with magnetic moments close to the expected spin only magnetic moments of Cr(+3) and Mn(+3). The UV-Visible diffuse reflectance spectra are broad and indicate that these materials possess a bandgap of similar to 2 eV. The photocatalytic activity of these materials has been investigated by degrading Malachite Green (MG) under exposure to UV light.

Accurate Parameter Estimation of Contaminant Transport Inverse Problem using Paartaicle Swarm Optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

An Empirical Analysis of Heterogeneity in IEEE 802.11 MAC Protocol Implementations and its Implications

Wireless LAN (WLAN) market consists of IEEE 802.11 MAC standard conformant devices (e.g., access points (APs), client adapters) from multiple vendors. Certain third party certifications such as those specified by the Wi-Fi alliance have been widely used by vendors to ensure basic conformance to the 802.11 standard, thus leading to the expectation that the available devices exhibit identical MAC level behavior. In this paper, however, we present what we believe to be the first ever set of experimental results that highlight the fact that WLAN devices from different vendors in the market can have heterogeneous MAC level behavior. Specifically, we demonstrate with examples and data that in certain cases, devices may not be conformant with the 802.11 standard while in other cases, they may differ in significant details that are not a part of mandatory specifications of the standard. We argue that heterogeneous MAC implementations can adversely impact WLAN operations leading to unfair bandwidth allocation, potential break-down of related MAC functionality and difficulties in provisioning the capacity of a WLAN. However, on the positive side, MAC level heterogeneity can be useful in applications such as vendor/model level device fingerprinting.

The Case for Non-Cooperative Multihoming of Users to Access Points in IEEE 802.11 WLANs

In many cases, a mobile user has the option of connecting to one of several IEEE 802.11 access points (APs),each using an independent channel. User throughput in each AP is determined by the number of other users as well as the frame size and physical rate being used. We consider the scenario where users could multihome, i.e., split their traffic amongst all the available APs, based on the throughput they obtain and the price charged. Thus, they are involved in a non-cooperative game with each other. We convert the problem into a fluid model and show that under a pricing scheme, which we call the cost price mechanism, the total system throughput is maximized,i.e., the system suffers no loss of efficiency due to selfish dynamics. We also study the case where the Internet Service Provider (ISP) could charge prices greater than that of the cost price mechanism. We show that even in this case multihoming outperforms unihoming, both in terms of throughput as well as profit to the ISP.

An analytical model for an IEEE~802.11 WLAN using DCF with two types of VoIP calls

In this paper we develop and numerically explore the modeling heuristic of using saturation attempt probabilities as state dependent attempt probabilities in an IEEE 802.11e infrastructure network carrying packet telephone calls and TCP controlled file downloads, using enhanced distributed channel access (EDCA). We build upon the fixed point analysis and performance insights. When there are a certain number of nodes of each class contending for the channel (i.e., have nonempty queues), then their attempt probabilities are taken to be those obtained from saturation analysis for that number of nodes. Then we model the system queue dynamics at the network nodes. With the proposed heuristic, the system evolution at channel slot boundaries becomes a Markov renewal process, and regenerative analysis yields the desired performance measures. The results obtained from this approach match well with ns2 simulations. We find that, with the default IEEE 802.11e EDCA parameters for AC 1 and AC 3, the voice call capacity decreases if even one file download is initiated by some station. Subsequently, reducing the voice calls increases the file download capacity almost linearly (by 1/3 Mbps per voice call for the 11 Mbps PHY)

A comparison of three methods for downscaling daily precipitation in the Punjab region

Many downscaling techniques have been developed in the past few years for projection of station-scale hydrological variables from large-scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K-nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue-type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright (C) 2011 John Wiley & Sons, Ltd.

Studies of phosphazenes .11. syntheses and structures of bis(primary amino)hexachlorocyclotetraphosphazenes and their dimethylamino derivatives

The bis(amino)hexachlorocyclotetraphosphazenes, 2-trans-6-N4P4 (NHR)2Cl6, R [dbnd] Me, Pr n Pr i , Bu n , CH2Ph, Ph, are obtained from the reaction of N4P4Cl8 with four mol. equivalents of the appropriate amine. Isomers with 2,4-structures have been isolated for R [dbnd] Bu n , CH2Ph. The 1H and 31P NMR spectra of these bis(amino) compounds and of their dimethylamino derivatives, 2-trans-6-N4P4 (NMe2)6 (NHR)2 are discussed.

A Rhodanine Derivative CCR-11 Inhibits Bacterial Proliferation by Inhibiting the Assembly and GTPase Activity of FtsZ

A perturbation of FtsZ assembly dynamics has been shown to inhibit bacterial cytokinesis. In this study, the antibacterial activity of 151 rhodanine compounds was assayed using Bacillus subtilis cells. Of 151 compounds, eight strongly inhibited bacterial proliferation at 2 mu M. Subsequently, we used the elongation of B. subtilis cells as a secondary screen to identify potential FtsZ-targeted antibacterial agents. We found that three compounds significantly increased bacterial cell length. One of the three compounds, namely, CCR-11 (E)-2-thioxo-5-({3-(trifluoromethyl)phenyl]furan-2-yl}methylene) thiazolidin-4-one], inhibited the assembly and GTPase activity of FtsZ in vitro. CCR-11 bound to FtsZ with a dissociation constant of 1.5 +/- 0.3 mu M. A docking analysis indicated that CCR-11 may bind to FtsZ in a cavity adjacent to the T7 loop and that short halogen oxygen, H-bonding, and hydrophobic interactions might be important for the binding of CCR-11 with FtsZ. CCR-11 inhibited the proliferation of B. subtilis cells with a half-maximal inhibitory concentration (IC50) of 1.2 +/- 0.2 mu M and a minimal inhibitory concentration of 3 mu M. It also potently inhibited proliferation of Mycobacterium smegmatis cells. Further, CCR-11 perturbed Z-ring formation in B. subtilis cells; however, it neither visibly affected nucleoid segregation nor altered the membrane integrity of the cells. CCR-11 inhibited HeLa cell proliferation with an IC50 value of 18.1 +/- 0.2,mu M (similar to 15 x IC50 of B. subtilis cell proliferation). The results suggested that CCR-11 inhibits bacterial cytokinesis by inhibiting FtsZ assembly, and it can be used as a lead molecule to develop FtsZ-targeted antibacterial agents.

State Dependent Attempt Rate modeling of single cell IEEE 802.11 WLANs with homogeneous nodes and Poisson packet arrivals

We study a State Dependent Attempt Rate (SDAR) approximation to model M queues (one queue per node) served by the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol as standardized in the IEEE 802.11 Distributed Coordination Function (DCF). The approximation is that, when n of the M queues are non-empty, the (transmission) attempt probability of each of the n non-empty nodes is given by the long-term (transmission) attempt probability of n saturated nodes. With the arrival of packets into the M queues according to independent Poisson processes, the SDAR approximation reduces a single cell with non-saturated nodes to a Markovian coupled queueing system. We provide a sufficient condition under which the joint queue length Markov chain is positive recurrent. For the symmetric case of equal arrival rates and finite and equal buffers, we develop an iterative method which leads to accurate predictions for important performance measures such as collision probability, throughput and mean packet delay. We replace the MAC layer with the SDAR model of contention by modifying the NS-2 source code pertaining to the MAC layer, keeping all other layers unchanged. By this model-based simulation technique at the MAC layer, we achieve speed-ups (w.r.t. MAC layer operations) up to 5.4. Through extensive model-based simulations and numerical results, we show that the SDAR model is an accurate model for the DCF MAC protocol in single cells. (C) 2012 Elsevier B.V. All rights reserved.

Modeling the effect of transmission errors on TCP controlled transfers over infrastructure 802.11 wireless LANs

There have been several studies on the performance of TCP controlled transfers over an infrastructure IEEE 802.11 WLAN, assuming perfect channel conditions. In this paper, we develop an analytical model for the throughput of TCP controlled file transfers over the IEEE 802.11 DCF with different packet error probabilities for the stations, accounting for the effect of packet drops on the TCP window. Our analysis proceeds by combining two models: one is an extension of the usual TCP-over-DCF model for an infrastructure WLAN, where the throughput of a station depends on the probability that the head-of-the-line packet at the Access Point belongs to that station; the second is a model for the TCP window process for connections with different drop probabilities. Iterative calculations between these models yields the head-of-the-line probabilities, and then, performance measures such as the throughputs and packet failure probabilities can be derived. We find that, due to MAC layer retransmissions, packet losses are rare even with high channel error probabilities and the stations obtain fair throughputs even when some of them have packet error probabilities as high as 0.1 or 0.2. For some restricted settings we are also able to model tail-drop loss at the AP. Although involving many approximations, the model captures the system behavior quite accurately, as compared with simulations.