Synthesis of Al and Ag nanoparticles through ultra-sonic dissociation of thermal evaporation deposited thin films for promising clinical applications as polymer nanocomposite

Nanoparticles (NPs) having well-defined shape, size and clean surface serve as ideal model system to investigate surface/interfacial reactions. Ag and Al NPs are receiving great interest due to their wide applications in bio-medical field, aerospace and space technology as combustible additives in propellants and hydrogen generation. Hence, in this study, we have synthesized Ag and Al NPs using an innovative approach of ultra-sonic dissociation of thin films. Phase and particle size distributions of the Ag and Al NPs have been determined by X-ray diffraction (XRD) and transmission electron microscopy (TEM). Thin film dissociation/dissolution mechanism, hence conversion into NPs has been characterized by SEM- scanning electron microscope. EDXA & ICPMS have been performed for chemical analysis of NPs. Optical properties have been characterized by UV-Vis and PL spectroscopy. These NPs have also been investigated for their anti-bacterial activity against Escherichia coli bacteria. To the best of our knowledge, this is the first time when NPs has been synthesized by ultra-sonic dissociation of thin films. As an application, these NPs were used further for synthesis of nanocomposite polymer membranes, which show excellent activity against bio film formation

Cathepsin-Sensitive Nanoscale Drug Delivery Systems for Cancer Therapy and other Diseases

International audienc

Secure Communication in Dynamic Incomplete Networks

In this paper, we explore the feasibility of reliable and private communication in dynamic networks, where in each round the adversary can choose which direct peer-to-peer links are available in the network graph, under the sole condition that the graph is k-connected at each round (for some k). We show that reliable communication is possible in such a dynamic network if and only if k > 2t. We also show that if k = cn > 2 t for a constant c, we can achieve reliable communication with polynomial round and communication complexity. For unconditionally private communication, we show that for a passive adversary, k > t is sufficient (and clearly necessary). For an active adversary, we show that k > 2t is sufficient for statistical security (and clearly necessary), while k > 3t is sufficient for perfect security. We conjecture that, in contrast to the static case, k > 2t is not enough for perfect security, and we give evidence that the conjecture is true. Once we have reliable and private communication between each pair of parties, we can emulate a complete network with secure channels, and we can use known protocols to do secure computation

Single Object Tracking System By Using Labview

Moving object detection is an interesting area in the field of video tracking. When the object is moving then tracking that is challenging task in vision area. This paper is about detecting, tracking of moving objects from the source. Many image processing methods to detect and track the moving object from the source was proposed, but those methods require more time to implement and is complex. This paper gives information about the moving object detection based on the tracking mean shift algorithm. LABVIEW vision module introduces a recent algorithm for object detection and tracking, in this algorithm current location is searched based on the histogram of the object in the previous image frame and result of mean shift is used to find the peak of probability density function near the object old position. Initial location of the target object need to be determined for this to work correctly. Mean shift is an effective algorithm that has so many application especially in the field of computer vision like clustering, object contour detection etc

Bit Based Approximation for Approx-NoC: A Data Approximation Framework for Network-On-Chip Architectures

The dawn of the big data era has led to the inception of new and creative compute paradigms that utilize heterogeneity, specialization, processor-in-memory and approximation due to the high demand for memory bandwidth and power. Relaxing the constraints of applications has led to approximate computing being put forth as a feasible solution for high performance computation. The latest fad such as machine learning, video/image processing, data analytics, neural networks and other data intensive applications have heightened the possibility of using approximate computing as a feasible solution as these applications allow imprecise output within a specific error range. This work presents Bit Based Approx-NoC, a hardware data approximation framework with a lightweight bit-based approximation technique for high performance NoCs. Bit-Based Approx-NoC facilitates approximate matching of data patterns, within a controllable error range, to compress them thereby reducing the data movement across the chip. The proposed work exploits the entropy between data words in order to increase their inherent compressibility. Evaluations in this work show on average 5% latency reduction and 14% throughput improvement compared to the state of the art NoC compression mechanisms

A Novel Signal Processing Measure to Identify Exact and Inexact Tandem Repeat Patterns in DNA Sequences

The identification and analysis of repetitive patterns are active areas of biological and computational research. Tandem repeats in telomeres play a role in cancer and hypervariable trinucleotide tandem repeats are linked to over a dozen major neurodegenerative genetic disorders. In this paper, we present an algorithm to identify the exact and inexact repeat patterns in DNA sequences based on orthogonal exactly periodic subspace decomposition technique. Using the new measure our algorithm resolves the problems like whether the repeat pattern is of period P or its multiple (i.e., 2P, 3P, etc.), and several other problems that were present in previous signal-processing-based algorithms. We present an efficient algorithm of O(NLw logLw), where N is the length of DNA sequence and Lw is the window length, for identifying repeats. The algorithm operates in two stages. In the first stage, each nucleotide is analyzed separately for periodicity, and in the second stage, the periodic information of each nucleotide is combined together to identify the tandem repeats. Datasets having exact and inexact repeats were taken up for the experimental purpose. The experimental result shows the effectiveness of the approach

Round-Optimal Multi-party Computation with Identifiable Abort

Secure multi-party computation (MPC) protocols that are resilient to a dishonest majority allow the adversary to get the output of the computation while, at the same time, forcing the honest parties to abort. Aumann and Lindell introduced the enhanced notion of security with identifiable abort, which still allows the adversary to trigger an abort but, at the same time, it enables the honest parties to agree on the identity of the party that led to the abort. More recently, in Eurocrypt 2016, Garg et al. showed that, assuming access to a simultaneous message exchange channel for all the parties, at least four rounds of communication are required to securely realize non-trivial functionalities in the plain model. Following Garg et al., a sequence of works has matched this lower bound, but none of them achieved security with identifiable abort. In this work, we close this gap and show that four rounds of communication are also sufficient to securely realize any functionality with identifiable abort using standard and generic polynomial-time assumptions. To achieve this result we introduce the new notion of bounded-rewind secure MPC that guarantees security even against an adversary that performs a mild form of reset attacks. We show how to instantiate this primitive starting from any MPC protocol and by assuming trapdoor-permutations. The notion of bounded-rewind secure MPC allows for easier parallel composition of MPC protocols with other (interactive) cryptographic primitives. Therefore, we believe that this primitive can be useful in other contexts in which it is crucial to combine multiple primitives with MPC protocols while keeping the round complexity of the final protocol low

Emergence of resistance to linezolid in methicillin resistant Staphylococcus haemolyticus reported from the sub Himalayan region of India

The spread of resistance among coagulase negative Staphylococci against major drugs is alarming as it limits the treatment options for serious infections. Resistance to linezolid in these organisms is emerging and further compounded by being observed in multidrug resistant strains. It is the only antibiotic available as an oral formulation for resistant Staphylococcal infections and due to the presence of a novel structure and unique mechanism of action, it does not display cross resistance with other classes of antimicrobial agents. However, the widespread use of Linezolid has gradually turned the impending fear of emergence of resistance against this novel drug into a reality. Herein we report a case of sepsis due to methicillin resistant Staphylococcus haemolyticus in a 16-year-old male child found resistant to linezolid, rarely reported from Sub Himalayan region of Indian sub-continent

Assumption Generation for the Verification of Learning-Enabled Autonomous Systems

Providing safety guarantees for autonomous systems is difficult as these systems operate in complex environments that require the use of learning-enabled components, such as deep neural networks (DNNs) for visual perception. DNNs are hard to analyze due to their size (they can have thousands or millions of parameters), lack of formal specifications (DNNs are typically learnt from labeled data, in the absence of any formal requirements), and sensitivity to small changes in the environment. We present an assume-guarantee style compositional approach for the formal verification of system-level safety properties of such autonomous systems. Our insight is that we can analyze the system in the absence of the DNN perception components by automatically synthesizing assumptions on the DNN behaviour that guarantee the satisfaction of the required safety properties. The synthesized assumptions are the weakest in the sense that they characterize the output sequences of all the possible DNNs that, plugged into the autonomous system, guarantee the required safety properties. The assumptions can be leveraged as run-time monitors over a deployed DNN to guarantee the safety of the overall system; they can also be mined to extract local specifications for use during training and testing of DNNs. We illustrate our approach on a case study taken from the autonomous airplanes domain that uses a complex DNN for perception

MPC with Low Bottleneck-Complexity: Information-Theoretic Security and More

The bottleneck-complexity (BC) of secure multiparty computation (MPC) protocols is a measure of the maximum number of bits which are sent and received by any party in protocol. As the name suggests, the goal of studying BC-efficient protocols is to increase overall efficiency by making sure that the workload in the protocol is somehow "amortized" by the protocol participants. Orlandi et al. [Orlandi et al., 2022] initiated the study of BC-efficient protocols from simple assumptions in the correlated randomness model and for semi-honest adversaries. In this work, we extend the study of [Orlandi et al., 2022] in two primary directions: (a) to a larger and more general class of functions and (b) to the information-theoretic setting. In particular, we offer semi-honest secure protocols for the useful function classes of abelian programs, "read-k" non-abelian programs, and "read-k" generalized formulas. Our constructions use a novel abstraction, called incremental function secret-sharing (IFSS), that can be instantiated with unconditional security or from one-way functions (with different efficiency trade-offs)