96 resultados para Distinguishing Attack
Resumo:
A robust suboptimal reentry guidance scheme is presented for a reusable launch vehicle using the recently developed, computationally efficient model predictive static programming. The formulation uses the nonlinear vehicle dynamics with a spherical and rotating Earth, hard constraints for desired terminal conditions, and an innovative cost function having several components with associated weighting factors that can account for path and control constraints in a soft constraint manner, thereby leading to smooth solutions of the guidance parameters. The proposed guidance essentially shapes the trajectory of the vehicle by computing the necessary angle of attack and bank angle that the vehicle should execute. The path constraints are the structural load constraint, thermal load constraint, bounds on the angle of attack, and bounds on the bank angle. In addition, the terminal constraints include the three-dimensional position and velocity vector components at the end of the reentry. Whereas the angle-of-attack command is generated directly, the bank angle command is generated by first generating the required heading angle history and then using it in a dynamic inversion loop considering the heading angle dynamics. Such a two-loop synthesis of bank angle leads to better management of the vehicle trajectory and avoids mathematical complexity as well. Moreover, all bank angle maneuvers have been confined to the middle of the trajectory and the vehicle ends the reentry segment with near-zero bank angle, which is quite desirable. It has also been demonstrated that the proposed guidance has sufficient robustness for state perturbations as well as parametric uncertainties in the model.
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We present a multipartite protocol in a counterfactual paradigm. In counterfactual quantum cryptography, secure information is transmitted between two spatially separated parties even when there is no physical travel of particles transferring the information between them. We propose here a tripartite counterfactual quantum protocol for the task of certificate authorization. Here a trusted third party, Alice, authenticates an entity Bob (e.g., a bank) that a client Charlie wishes to securely transact with. The protocol is counterfactual with respect to either Bob or Charlie. We prove its security against a general incoherent attack, where Eve attacks single particles.
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In continuation of our interest in pyrazole based multifunctional metal-organic frameworks (MOFs), we report herein the construction of a series of Co(II) MOFs using a bis-pyrazole ligand and various benzene polycarboxylic acids. Employment of different acids has resulted in different architectures ranging from a two-dimensional grid network, porous nanochannels with interesting double helical features such as supramolecular chicken wire, to three-dimensional diamondoid networks. One of the distinguishing features of the network is their larger dimensions which can be directly linked to a relatively larger size of the ligand molecule. Conformational flexibility of the ligand also plays a decisive role in determining both the dimensionality and topology of the final structure. Furthermore, chirality associated with helical networks and magnetic properties of two MOFs have also been investigated.
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Thermal decomposition of propargyl alcohol (C3H3OH), a molecule of interest in interstellar chemistry and combustion, was investigated using a single pulse shock tube in the temperature ranging from 953 to 1262 K. The products identified include acetylene, propyne, vinylacetylene, propynal, propenal, and benzene. The experimentally observed overall rate constant for thermal decomposition of propargyl alcohol was found to be k = 10((10.17 +/- 0.36)) exp(-39.70 +/- 1.83)/RT) s(-1) Ab initio theoretical calculations were carried out to understand the potential energy surfaces involved in the primary and secondary steps of propargyl alcohol thermal decomposition. Transition state theory was used to predict the rate constants, which were then used and refined in a kinetic simulation of the product profile. The first step in the decomposition is C-O bond dissociation, leading to the formation of two important radicals in combustion, OH and propargyl. This has been used to study the reverse OH propargyl radical reaction, about which there appears to be no prior work. Depending on the site of attack, this reaction leads to propargyl alcohol or propenal, one of the major products at temperatures below 1200 K. A detailed mechanism has been derived to explain all the observed products.
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Decarboxylative thioesterification of isatoic anhydrides mediated by benzyl(triethyl)ammonium tetrathiomolybdate gave the corresponding S-alkyl or S-aryl 2-aminobenzenecarbothioate derivatives at 60 degrees C. At ambient temperature, organic disulfides were reductive cleaved in the presence of tetrathiomolybdate to generate thiolate anions in situ; this was followed by attack on isatoic anhydrides to give the corresponding S-alkyl or S-aryl 2-aminobenzenecarbothioate derivatives. Additionally, it was shown that multistep reactions could be performed with tetrathiomolybdate, starting with an alkyl halide as a precursor of an alkyl disulfide, which, in turn, was used for ring opening of isatoic anhydrides.
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User authentication is essential for accessing computing resources, network resources, email accounts, online portals etc. To authenticate a user, system stores user credentials (user id and password pair) in system. It has been an interested field problem to discover user password from a system and similarly protecting them against any such possible attack. In this work we show that passwords are still vulnerable to hash chain based and efficient dictionary attacks. Human generated passwords use some identifiable patterns. We have analysed a sample of 19 million passwords, of different lengths, available online and studied the distribution of the symbols in the password strings. We show that the distribution of symbols in user passwords is affected by the native language of the user. From symbol distributions we can build smart and efficient dictionaries, which are smaller in size and their coverage of plausible passwords from Key-space is large. These smart dictionaries make dictionary based attacks practical.
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The transformation of flowing liquids into rigid glasses is thought to involve increasingly cooperative relaxation dynamics as the temperature approaches that of the glass transition. However, the precise nature of this motion is unclear, and a complete understanding of vitrification thus remains elusive. Of the numerous theoretical perspectives(1-4) devised to explain the process, random first-order theory (RFOT; refs 2,5) is a well-developed thermodynamic approach, which predicts a change in the shape of relaxing regions as the temperature is lowered. However, the existence of an underlying `ideal' glass transition predicted by RFOT remains debatable, largely because the key microscopic predictions concerning the growth of amorphous order and the nature of dynamic correlations lack experimental verification. Here, using holographic optical tweezers, we freeze a wall of particles in a two-dimensional colloidal glass-forming liquid and provide direct evidence for growing amorphous order in the form of a static point-to-set length. We uncover the non-monotonic dependence of dynamic correlations on area fraction and show that this non-monotonicity follows directly from the change in morphology and internal structure of cooperatively rearranging regions(6,7). Our findings support RFOT and thereby constitute a crucial step in distinguishing between competing theories of glass formation.
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The de novo purine biosynthesis is one of the highly conserved pathways among all organisms and is essential for the cell viability. A clear understanding of the enzymes in this pathway would pave way for the development of antimicrobial and anticancer drugs. Phosphoribosylaminoimidazole-succinocar boxamide (SAICAR) synthetase is one of the enzymes in this pathway that catalyzes ATP dependent ligation of carboxyaminoimidazole ribotide (CAIR) with L-aspartate (ASP). Here, we describe eight crystal structures of this enzyme, in C222(1) and H3 space groups, bound to various substrates and substrate mimics from a hyperthermophilic archaea Pyrococcus horikoshii along with molecular dynamics simulations of the structures with substrates. Complexes exhibit minimal deviation from its apo structure. The CAIR binding site displays a preference for pyrimidine nucleotides. In the ADP.TMP-ASP complex, the ASP binds at a position equivalent to that found in Saccharomyces cerevisiae structure (PDB: 2CNU) and thus, clears the ambiguity regarding ASP's position. A possible mode for the inhibition of the enzyme by CTP and UTP, observed earlier in the yeast enzyme, is clearly illustrated in the structures bound to CMP and UMP. The ADP.Mg2+.PO4.CD/MP complex having a phosphate ion between the ATP and CAIR sites strengthens one of the two probable pathways (proposed in Escherichia coli study) of catalytic mechanism and suggests the possibility of a phosphorylation taking place before the ASP's attack on CAIR. Molecular dynamic simulations of this enzyme along with its substrates at 90 degrees C reveal the relative strengths of substrate binding, possible antagonism and the role of Mg2+ ions. (C) 2015 Elsevier Inc. All rights reserved.
Resumo:
Wrist pulse signal contains more important information about the health status of a person and pulse signal diagnosis has been employed in oriental medicine since very long time. In this paper we have used signal processing techniques to extract information from wrist pulse signals. For this purpose we have acquired radial artery pulse signals at wrist position noninvasively for different cases of interest. The wrist pulse waveforms have been analyzed using spatial features. Results have been obtained for the case of wrist pulse signals recorded for several subjects before exercise and after exercise. It is shown that the spatial features show statistically significant changes for the two cases and hence they are effective in distinguishing the changes taking place due to exercise. Support vector machine classifier is used to classify between the groups, and a high classification accuracy of 99.71% is achieved. Thus this paper demonstrates the utility of the spatial features in studying wrist pulse signals obtained under various recording conditions. The ability of the model to distinguish changes occurring under two different recording conditions can be potentially used for health care applications.
Resumo:
It is well known that wrist pulse signals contain information about the status of health of a person and hence diagnosis based on pulse signals has assumed great importance since long time. In this paper the efficacy of signal processing techniques in extracting useful information from wrist pulse signals has been demonstrated by using signals recorded under two different experimental conditions viz. before lunch condition and after lunch condition. We have used Pearson's product-moment correlation coefficient, which is an effective measure of phase synchronization, in making a statistical analysis of wrist pulse signals. Contour plots and box plots are used to illustrate various differences. Two-sample t-tests show that the correlations show statistically significant differences between the groups. Results show that the correlation coefficient is effective in distinguishing the changes taking place after having lunch. This paper demonstrates the ability of the wrist pulse signals in detecting changes occurring under two different conditions. The study assumes importance in view of limited literature available on the analysis of wrist pulse signals in the case of food intake and also in view of its potential health care applications.
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Wrist pulse signals contain important information about the health of a person and hence diagnosis based on pulse signals has assumed great importance. In this paper we demonstrate the efficacy of a two term Gaussian model to extract information from pulse signals. Results have been obtained by conducting experiments on several subjects to record wrist pulse signals for the cases of before exercise and after exercise. Parameters have been extracted from the recorded signals using the model and a paired t-test is performed, which shows that the parameters are significantly different between the two groups. Further, a recursive cluster elimination based support vector machine is used to perform classification between the groups. An average classification accuracy of 99.46% is obtained, along with top classifiers. It is thus shown that the parameters of the Gaussian model show changes across groups and hence the model is effective in distinguishing the changes taking place due to the two different recording conditions. The study has potential applications in healthcare.
Resumo:
Reactive oxygen species (ROS)-mediated diseased states are of major concern in modern day life. Under oxidative stress conditions, the cellular antioxidants deplete, leading to several biological disorders. Small molecule mimics of different antioxidant enzymes are found to be useful in supplementing the biological systems to detoxify ROS. In this study, we have synthesized a series of amine or amide-based diselenides containing an additional amino group as glutathione peroxidase (GPx) mimetics. These diselenides act as a catalytic triad model of the native GPx featuring two basic amino groups near the selenium centre. A comparison of the catalytic activities reveals that the additional amino group increases the activity significantly in the presence of aromatic thiols. Deprotonation of thiol by an additional amine either stabilizes the selenolate intermediate or facilitates the nucleophilic attack of thiol in other intermediates. The Se-77 NMR experiments and DFT calculations show that the amino group does not have any significant effect on the catalytic intermediates. Although the amino moiety increases the nucleophilicity of the thiol, it does not prevent the thiol exchange reactions that take place in the selenenyl sulfide intermediates.
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Glioblastomas (GBM) are largely incurable as they diffusely infiltrate adjacent brain tissues and are difficult to diagnose at early stages. Biomarkers derived from serum, which can be obtained by minimally invasive procedures, may help in early diagnosis, prognosis and treatment monitoring. To develop a serum cytokine signature, we profiled 48 cytokines in sera derived from normal healthy individuals (n = 26) and different grades of glioma patients (n = 194). We divided the normal and grade IV glioma/GBM serum samples randomly into equal sized training and test sets. In the training set, the Prediction Analysis for Microarrays (PAM) identified a panel of 18 cytokines that could discriminate GBM sera fromnormal sera with maximum accuracy (95.40%) and minimum error (4.60%). The 18-cytokine signature obtained in the training set discriminated GBM sera from normal sera in the test set as well (accuracy 96.55%; error 3.45%). Interestingly, the 18-cytokine signature also differentiated grade II/Diffuse Astrocytoma (DA) and grade III/Anaplastic Astrocytoma (AA) sera from normal sera very efficiently (DA vs. normal-accuracy 96.00%, error 4.00%; AA vs. normal-accuracy 95.83%, error 4.17%). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis using 18 cytokines resulted in the enrichment of two pathways, cytokine-cytokine receptor interaction and JAK-STAT pathways with high significance. Thus our study identified an 18-cytokine signature for distinguishing glioma sera fromnormal healthy individual sera and also demonstrated the importance of their differential abundance in glioma biology.
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The transient changes in resistances of Cr0.8Fe0.2NbO4 thick film sensors towards specified concentrations of H-2, NH3, acetonitrile, acetone, alcohol, cyclohexane and petroleum gas at different operating temperatures were recorded. The analyte-specific characteristics such as slopes of the response and retrace curves, area under the curve and sensitivity deduced from the transient curve of the respective analyte gas have been used to construct a data matrix. Principal component analysis (PCA) was applied to this data and the score plot was obtained. Distinguishing one reducing gas from the other is demonstrated based on this approach, which otherwise is not possible by measuring relative changes in conductivity. This methodology is extended for three Cr0.8Fe0.2NbO4 thick film sensor array operated at different temperatures. (C) 2015 Elsevier B.V. All rights reserved.
Resumo:
Purpose: Composition of the coronary artery plaque is known to have critical role in heart attack. While calcified plaque can easily be diagnosed by conventional CT, it fails to distinguish between fibrous and lipid rich plaques. In the present paper, the authors discuss the experimental techniques and obtain a numerical algorithm by which the electron density (rho(e)) and the effective atomic number (Z(eff)) can be obtained from the dual energy computed tomography (DECT) data. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques. Methods: For the purpose of calibration of the CT machine, the authors prepare aqueous samples whose calculated values of (rho(e), Z(eff)) lie in the range of (2.65 x 10(23) <= rho(e) <= 3.64 x 10(23)/cm(3)) and (6.80 <= Z(eff) <= 8.90). The authors fill the phantom with these known samples and experimentally determine HU(V-1) and HU(V-2), with V-1,V-2 = 100 and 140 kVp, for the same pixels and thus determine the coefficients of inversion that allow us to determine (rho(e), Z(eff)) from the DECT data. The HU(100) and HU(140) for the coronary artery plaque are obtained by filling the channel of the coronary artery with a viscous solution of methyl cellulose in water, containing 2% contrast. These (rho(e), Z(eff)) values of the coronary artery plaque are used for their characterization on the basis of theoretical models of atomic compositions of the plaque materials. These results are compared with histopathological report. Results: The authors find that the calibration gives Pc with an accuracy of 3.5% while Z(eff) is found within 1% of the actual value, the confidence being 95%. The HU(100) and HU(140) are found to be considerably different for the same plaque at the same position and there is a linear trend between these two HU values. It is noted that pure lipid type plaques are practically nonexistent, and microcalcification, as observed in histopathology, has to be taken into account to explain the nature of the observed (rho(e), Z(eff)) data. This also enables us to judge the composition of the plaque in terms of basic model which considers the plaque to be composed of fibres, lipids, and microcalcification. Conclusions: This simple and reliable method has the potential as an effective modality to investigate the composition of noncalcified coronary artery plaques and thus help in their characterization. In this inversion method, (rho(e), Z(eff)) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (rho(e), Z(eff)) does not interfere with each other and the nature of the plaque can be identified in terms of a three component model. (C) 2015 American Association of Physicists in Medicine.