Efficient biometric and password based mutual authentication for consumer USB mass storage devices

A Universal Serial Bus (USB) Mass Storage Device (MSD), often termed a USB flash drive, is ubiquitously used to store important information in unencrypted binary format. This low cost consumer device is incredibly popular due to its size, large storage capacity and relatively high transfer speed. However, if the device is lost or stolen an unauthorized person can easily retrieve all the information. Therefore, it is advantageous in many applications to provide security protection so that only authorized users can access the stored information. In order to provide security protection for a USB MSD, this paper proposes a session key agreement protocol after secure user authentication. The main aim of this protocol is to establish session key negotiation through which all the information retrieved, stored and transferred to the USB MSD is encrypted. This paper not only contributes an efficient protocol, but also does not suffer from the forgery attack and the password guessing attack as compared to other protocols in the literature. This paper analyses the security of the proposed protocol through a formal analysis which proves that the information is stored confidentially and is protected offering strong resilience to relevant security attacks. The computational cost and communication cost of the proposed scheme is analyzed and compared to related work to show that the proposed scheme has an improved tradeoff for computational cost, communication cost and security.

The effect of financial leverage on real and accrual-based earnings management

Past research has documented a substitution effect between real earnings management (RM) and accrual-based earnings management (AM), depending on relative costs. This study contributes to this research by examining whether levels of (and changes in) financial leverage have an impact on this empirically documented trade-off. We hypothesise that in the presence of high leverage, firms that engage in earnings manipulation tactics will exhibit a preference for RM due to a lower possibility—and subsequent costs—of getting caught. We show that leverage levels and increases positively and significantly affect upward RM, with no significant effect on income-increasing AM, while our findings point towards a complementarity effect between unexpected levels of RM and AM for firms with very high leverage levels and changes. This is interpreted as an indication that high leverage could attract heavy outsider scrutiny, making it necessary for firms to use both forms of earnings management in order to achieve earnings targets. Furthermore, we document that equity investors exhibit a significantly stronger penalising reaction to AM vs. RM, indicating that leverage-induced RM is not as easily detectable by market participants as debt-induced AM, despite the fact that the former could imply deviation from optimal business practices.

Low-level Laser Therapy Improves Skeletal Muscle Performance, Decreases Skeletal Muscle Damage and Modulates mRNA Expression of COX-1 and COX-2 in a Dose-dependent Manner

We tested if modulation in mRNA expression of cyclooxygenase isoforms (COX-1 and COX-2) can be related to protective effects of phototherapy in skeletal muscle. Thirty male Wistar rats were divided into five groups receiving either one of four laser doses (0.1, 0.3, 1.0 and 3.0 J) or a no-treatment control group. Laser irradiation (904 nm, 15 mW average power) was performed immediately before the first contraction for treated groups. Electrical stimulation was used to induce six tetanic tibial anterior muscle contractions. Immediately after sixth contraction, blood samples were collected to evaluate creatine kinase activity and muscles were dissected and frozen in liquid nitrogen to evaluate mRNA expression of COX-1 and COX-2. The 1.0 and 3.0 J groups showed significant enhancement (P < 0.01) in total work performed in six tetanic contractions compared with control group. All laser groups, except the 3.0 J group, presented significantly lower post-exercise CK activity than control group. Additionally, 1.0 J group showed increased COX-1 and decreased COX-2 mRNA expression compared with control group and 0.1, 0.3 and 3.0 J laser groups (P < 0.01). We conclude that pre-exercise infrared laser irradiation with dose of 1.0 J enhances skeletal muscle performance and decreases post-exercise skeletal muscle damage and inflammation.

A new genotype of Trypanosoma cruzi associated with bats evidenced by phylogenetic analyses using SSU rDNA, cytochrome b and Histone H2B genes and genotyping based on ITS1 rDNA

We characterized 15 Trypanosoma cruzi isolates from bats captured in the Amazon, Central and Southeast Brazilian regions. Phylogenetic relationships among T. cruzi lineages using SSU rDNA, cytochrome b, and Histone H2B genes positioned all Amazonian isolates into T. cruzi I (TCI). However, bat isolates from the other regions, which had been genotyped as T. cruzi II (TC II) by the traditional genotyping method based on mini-exon gene employed in this study, Were not nested within any of the previously defined TCII sublineages, constituting a new genotype designated as TCbat. Phylogenetic analyses demonstrated that TCbat indeed belongs to T. cruzi and not to other closely related bat trypanosomes of the subgenus Schizotrypanum, and that although separated by large genetic distances TO-tat is closest to lineage TCI. A genotyping method targeting ITS1 rDNA distinguished TCbat from established T. cruzi lineages, and from other Schizotrypanum species. In experimentally infected mice, TCbat lacked virulence and yielded loss parasitaemias. Isolates of TCbat presented distinctive morphological features and behaviour in triatomines. To date, TCbat genotype wall found only in bats from anthropic environments of Central and Southeast Brazil. Our findings indicate that the complexity of T. cruzi is larger than currently known, and confirmed bats as important reservoirs and potential source of T. cruzi infections to humans.

MODELING THE EVOLUTION OF COMPLEX NETWORKS THROUGH THE PATH-STAR TRANSFORMATION AND OPTIMAL MULTIVARIATE METHODS

The topology of real-world complex networks, such as in transportation and communication, is always changing with time. Such changes can arise not only as a natural consequence of their growth, but also due to major modi. cations in their intrinsic organization. For instance, the network of transportation routes between cities and towns ( hence locations) of a given country undergo a major change with the progressive implementation of commercial air transportation. While the locations could be originally interconnected through highways ( paths, giving rise to geographical networks), transportation between those sites progressively shifted or was complemented by air transportation, with scale free characteristics. In the present work we introduce the path-star transformation ( in its uniform and preferential versions) as a means to model such network transformations where paths give rise to stars of connectivity. It is also shown, through optimal multivariate statistical methods (i.e. canonical projections and maximum likelihood classification) that while the US highways network adheres closely to a geographical network model, its path-star transformation yields a network whose topological properties closely resembles those of the respective airport transportation network.

Calixarene and Resorcarene Based Receptors: From Structural and Thermodynamic Studies to the Synthesis of a New Mercury(II) Selective Material

Materials used in current technological approaches for the removal of mercury lack selectivity. Given that this is one of the main features of supramolecular chemistry, receptors based on calix[4]arene and calix[4]resorcarene containing functional groups able to interact selectively with polluting ions while discriminating against biologically essential ones were designed. Thus two receptors, a partially functionalized calix[4]arene derivative, namely, 5,11,17,23-tetra-tert-butyl [25-27-bis(diethyl thiophosphate amino)dihydroxy] calix[4]arene (1) and a fully functionalized calix[4]resorcarene, 4,6,10,12,16,18,22,24-diethyl thiophosphate calix[4]resorcarene (2) are introduced. Mercury(II) was the identified target due to the environmental and health problems associated with its presence in water Thus following the synthesis and characterization of 1 and 2 in solution ((1)HNMR) and in the solid state (X-ray crystallography) the sequence of experimental events leading to cation complexation studies in acetonitrile and methanol ((1)H NMR, conductance, potentiometric, and calorimetric measurements) with the aim of assessing their behavior as mercury selective receptors are described. The cation selectivity pattern observed in acetonitrile follows the sequence Hg(II) > Cu(II) > Ag(I). In methanol 1 is also selective for Hg(II) relative to Ag(I) but no interaction takes place between this receptor and Cu(II) in this solvent. Based on previous results and experimental facts shown in this paper, it is concluded that the complexation observed with Cu(II) in acetonitrile occurs through the acetonitrile-receptor adduct rather than through the free ligand. Receptor 2 has an enhanced capacity for uptaking Hg(II) but forms metalate complexes with Cu(II). These studies in solution guided the inmobilization of receptor 1 into a silica support to produce a new and recyclable material for the removal of Hg(II) from water. An assessment on its capacity to extract this cation from water relative to Cu(II) and Ag (I) shows that the cation selectivity pattern of the inmobilized receptor is the same as that observed for the free receptor in methanol. These findings demonstrate that fundamental studies play a critical role in the selection of the receptor to be attached to silicates as well as in the reaction medium used for the synthesis of the new decontaminating agent.

Natural products biological screening and ligand-based virtual screening for the discovery of new antileishmanial agents

In the course of our research program to discover novel antileishmanial agents, a biological screening of natural products against Leishmania major promastigotes allowed the identification of a furoquinoline alkaloid (1) and a furanocoumarin (2) as new hits. Subsequently, an integrated ligand-based virtual screening approach was employed to search for new antileishmanial compounds using these naturally occurring molecules as templates. Fourteen out of 40 compounds selected from a database of about 800,000 compounds (extracted from ZINC, a free database for virtual screening) were experimentally confirmed to possess significant in vitro antileishmanial properties. The application of ligand-based virtual screening as a complementary approach to experimental natural product screening was a useful strategy to facilitate the identification of new promising lead candidates.

Classical and fragment-based hologram structure-activity relationships for a series of analgesic cyclic imides

Cyclic imides have been widely employed in drug design research due to their multiple pharmacological and biological properties. In the present study, two-dimensional quantitative structure-activity relationship (2D QSAR) studies were conducted on a series of potent analgesic cyclic imides using both classical and hologram QSAR (HQSAR) methods, yielding significant statistical models (classical QSAR, q(2) = 0.80; HQSAR, q(2) = 0.84). The models were then used to evaluate an external data test, and the predicted values were in good agreement with the experimental results, indicating their consistency for untested compounds.

Integration of Ligand- and Target-Based Virtual Screening for the Discovery of Cruzain Inhibitors

A myriad of methods are available for virtual screening of small organic compound databases. In this study we have successfully applied a quantitative model of consensus measurements, using a combination of 3D similarity searches (ROCS and EON), Hologram Quantitative Structure Activity Relationships (HQSAR) and docking (FRED, FlexX, Glide and AutoDock Vina), to retrieve cruzain inhibitors from collected databases. All methods were assessed individually and then combined in a Ligand-Based Virtual Screening (LBVS) and Target-Based Virtual Screening (TBVS) consensus scoring, using Receiving Operating Characteristic (ROC) curves to evaluate their performance. Three consensus strategies were used: scaled-rank-by-number, rank-by-rank and rank-by-vote, with the most thriving the scaled-rank-by-number strategy, considering that the stiff ROC curve appeared to be satisfactory in every way to indicate a higher enrichment power at early retrieval of active compounds from the database. The ligand-based method provided access to a robust and predictive HQSAR model that was developed to show superior discrimination between active and inactive compounds, which was also better than ROCS and EON procedures. Overall, the integration of fast computational techniques based on ligand and target structures resulted in a more efficient retrieval of cruzain inhibitors with desired pharmacological profiles that may be useful to advance the discovery of new trypanocidal agents.

Simple telemedicine for developing regions: Camera phones and paper-based microfluidic devices for real-time, off-site diagnosis

This article describes a prototype system for quantifying bioassays and for exchanging the results of the assays digitally with physicians located off-site. The system uses paper-based microfluidic devices for running multiple assays simultaneously, camera phones or portable scanners for digitizing the intensity of color associated with each colorimetric assay, and established communications infrastructure for transferring the digital information from the assay site to an off-site laboratory for analysis by a trained medical professional; the diagnosis then can be returned directly to the healthcare provider in the field. The microfluidic devices were fabricated in paper using photolithography and were functionalized with reagents for colorimetric assays. The results of the assays were quantified by comparing the intensities of the color developed in each assay with those of calibration curves. An example of this system quantified clinically relevant concentrations of glucose and protein in artificial urine. The combination of patterned paper, a portable method for obtaining digital images, and a method for exchanging results of the assays with off-site diagnosticians offers new opportunities for inexpensive monitoring of health, especially in situations that require physicians to travel to patients (e.g., in the developing world, in emergency management, and during field operations by the military) to obtain diagnostic information that might be obtained more effectively by less valuable personnel.

Optical Characterization and Optimization of Display Components : Some Applications to Liquid-Crystal-Based and Electrochromics-Based Devices

This dissertation is focused on theoretical and experimental studies of optical properties of materials and multilayer structures composing liquid crystal displays (LCDs) and electrochromic (EC) devices. By applying spectroscopic ellipsometry, we have determined the optical constants of thin films of electrochromic tungsten oxide (WOx) and nickel oxide (NiOy), the films’ thickness and roughness. These films, which were obtained at spattering conditions possess high transmittance that is important for achieving good visibility and high contrast in an EC device. Another application of the general spectroscopic ellipsometry relates to the study of a photo-alignment layer of a mixture of azo-dyes SD-1 and SDA-2. We have found the optical constants of this mixture before and after illuminating it by polarized UV light. The results obtained confirm the diffusion model to explain the formation of the photo-induced order in azo-dye films. We have developed new techniques for fast characterization of twisted nematic LC cells in transmissive and reflective modes. Our techniques are based on the characteristics functions that we have introduced for determination of parameters of non-uniform birefringent media. These characteristic functions are found by simple procedures and can be utilised for simultaneous determination of retardation, its wavelength dispersion, and twist angle, as well as for solving associated optimization problems. Cholesteric LCD that possesses some unique properties, such as bistability and good selective scattering, however, has a disadvantage – relatively high driving voltage (tens of volts). The way we propose to reduce the driving voltage consists of applying a stack of thin (~1µm) LC layers. We have studied the ability of a layer of a surface stabilized ferroelectric liquid crystal coupled with several retardation plates for birefringent color generation. We have demonstrated that in order to accomplish good color characteristics and high brightness of the display, one or two retardation plates are sufficient.

Predictive models for chronic renal disease using decision trees, naïve bayes and case-based methods

Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.