Vortex Matter in Highly Strained Nb$$_{}$$Zr$$_{25}$$25: Analogy with Viscous Flow of Disordered Solids

We present the results of magnetization and magneto-transport measurements in the superconducting state of an as-cast Nb\(_{75}\)Zr\(_{25}\) alloy. We also report the microstructure of our sample at various length scales by using optical, scanning electron and transmission electron microscopies. The information of microstructure is used to understand the flux pinning properties in the superconducting state within the framework of collective pinning. The magneto-transport measurements show a non-Arrhenius behaviour of the temperature- and field-dependent resistivity across the resistive transition and is understood in terms of a model for viscous flow of disordered solids which is popularly known as the ‘shoving model’. The activation energy for flux flow is assumed to be mainly the elastic energy stored in the flux-line lattice. The scaling of pinning force density indicates the presence of two pinning mechanisms of different origins. The elastic constants of the flux-line lattice are used to estimate the length scale of vortex lattice movement, or the volume displaced by the flux-line lattice. It appears that the vortex lattice displacement estimated from elastic energy considerations is of the same order of magnitude as that of the flux bundle hopping length during flux flow. Our results could provide possible directions for establishing a framework where vortex matter and glass-forming liquids or amorphous solids can be treated in a similar manner for understanding the phenomenon of viscous flow in disordered solids or more generally the pinning and depinning properties of elastic manifolds in random media. It is likely that the vortex molasses scenario is more suited to explain the vortex dynamics in conventional low-T\(_C\) superconductors.     

Intramolecular Locked Dithioalkylbithiophene‐Based Semiconductors for High‐Performance Organic Field‐Effect Transistors

New 3,3′‐dithioalkyl‐2,2′‐bithiophene ( SBT )‐based small molecular and polymeric semiconductors are synthesized by end‐capping or copolymerization with dithienothiophen‐2‐yl units. Single‐crystal, molecular orbital computations, and optical/electrochemical data indicate that the SBT core is completely planar, likely via S(alkyl)?S(thiophene) intramolecular locks. Therefore, compared to semiconductors based on the conventional 3,3′‐dialkyl‐2,2′‐bithiophene, the resulting SBT systems are planar (torsional angle <1°) and highly π‐conjugated. Charge transport is investigated for solution‐sheared films in field‐effect transistors demonstrating that SBT can enable good semiconducting materials with hole mobilities ranging from ≈0.03 to 1.7 cm² V^?1 s^?1. Transport difference within this family is rationalized by film morphology, as accessed by grazing incidence X‐ray diffraction experiments.     

Co-delivery of gemcitabine and simvastatin through PLGA polymeric nanoparticles for the treatment of pancreatic cancer: in-vitro characterization,cellular uptake,and pharmacokinetic studies

Despite the ongoing extensive research, cancer therapeutics still remains an area with unmet needs which is hampered by shortfall in the development of newer medicines. The present study discusses a nano-based combinational approach for treating solid tumor. Dual-loaded nanoparticles encapsulating gemcitabine HCl (GM) and simvastatin (SV) were fabricated by double emulsion solvent evaporation method and optimized. Optimized nanoparticles showed a particle size of 258?±?2.4?nm, polydispersity index of 0.32?±?0.052, and zeta potential of ?12.5?mV. The size and the morphology of the particles wee further confirmed by transmission electron microscopy (TEM) and scanning electron microscopy, respectively of the particles. The entrapment efficiency of GM and SV in the nanoparticles was 38.5?±?4.5% and 72.2?±?5.6%, respectively. The in vitro release profile was studied for 60?h and showed Higuchi release pattern. The cell toxicity was done using MTT assay and lower IC₅₀ was obtained with the nanoparticles as compared to the pure drug. The bioavailability of GM and SV in PLGA nanoparticles was enhanced by 1.4-fold and 1.3-fold respectively, compared to drug solution. The results revealed that co-delivery of GM and SV could be used for its oral delivery for the effective treatment of pancreatic cancer.     

Pair Interaction between Two Catalytically Active Colloids

Due to the intrinsically complex non-equilibrium behavior of the constituents of active matter systems, a comprehensive understanding of their collective properties is a challenge that requires systematic bottom–up characterization of the individual components and their interactions. For self-propelled particles, intrinsic complexity stems from the fact that the polar nature of the colloids necessitates that the interactions depend on positions and orientations of the particles, leading to a 2d − 1 dimensional configuration space for each particle, in d dimensions. Moreover, the interactions between such non-equilibrium colloids are generically non-reciprocal, which makes the characterization even more complex. Therefore, derivation of generic rules that enable us to predict the outcomes of individual encounters as well as the ensuing collective behavior will be an important step forward. While significant advances have been made on the theoretical front, such systematic experimental characterizations using simple artificial systems with measurable parameters are scarce. Here, two different contrasting types of colloidal microswimmers are studied, which move in opposite directions and show distinctly different interactions. To facilitate the extraction of parameters, an experimental platform is introduced in which these parameters are confined on a 1D track. Furthermore, a theoretical model for interparticle interactions near a substrate is developed, including both phoretic and hydrodynamic effects, which reproduces their behavior. For subsequent validation, the degrees of freedom are increased to 2D motion and resulting trajectories are predicted, finding remarkable agreement. These results may prove useful in characterizing the overall alignment behavior of interacting self-propelling active swimmer and may find direct applications in guiding the design of active-matter systems involving phoretic and hydrodynamic interactions.     

An improved block based copy-move forgery detection technique

Multimedia Tools and Applications - With the increase in demand for identification of authenticity of the digital images, researchers are widely studying the image forgery detection techniques....     

High Diversity Gain MIMO-Antenna for UWB Application with WLAN Notch Band Characteristic Including Human Interface Devices

Wireless Personal Communications - In this paper, a UWB–MIMO antenna with the WLAN band-notch (5.1–5.85&nbsp;GHz) characteristic is offered. This antenna consists of two radiated...     

Identity Based Broadcast Encryption Scheme with Shorter Decryption Keys for Open Networks

In Broadcast Encryption schemes, a sender can broadcast the encrypted message securely in a threatening network to a set of legitimate system users only. In IBE scheme any sender can encrypt the desired message using his/her identity without attaining the public key certificate. Here, we have presented an efficient ID-based broadcast encryption scheme (IBBE) for open networks. In this scheme, desired messages can be broadcasted to any subset of the users by any sender but only authorized receivers are capable in retrieving the encrypted messages. This scheme has shorter decryption keys in comparison with other primitive of IBBE scheme for open networks. Moreover, the proposed scheme intends to achieve the lower cost for computation as well as transmission in comparison to earlier existing IBBE schemes.

     

An Experimental Evaluation of Link Outage Due to Beam Wander in a Turbulent FSO Link

Wireless Personal Communications - Wireless communication using free space optics (FSO) is becoming attractive for data transmission purposes. However, the system performance gets affected by...     

A policy based framework for quality of service management in software defined networks

Growth in multimedia traffic over the Internet increases congestion in the network architecture. Software-Defined Networking (SDN) is a novel paradigm that solves the congestion problem and allows the network to be dynamic, intelligent, and it centrally controls the network devices. SDN has many advantages in comparison to traditional networks, such as separation of forwarding and control plane from devices, global centralized control, management of network traffic. We design a policy-based framework to enhance the Quality of Service (QoS) of multimedia traffic flows in a potential SDN environment. We phrase a max-flow-min-cost routing problem to determine the routing paths and presented a heuristic method to route the traffic flows in the network in polynomial time. The framework monitors the QoS parameters of traffic flows and identifies policy violations due to link congestion in the network. The introduced approach dynamically implements policy rules to SDN switches upon detection of policy violations and reroutes the traffic flows. The results illustrate that the framework achieves a reduction in end-to-end delay, average jitter, and QoS violated flows by 24%, 37%, and 25%, respectively, as compared to the Delay Minimization method. Furthermore, the proposed approach has achieved better results when compared to SDN without policy-based framework and reduced end-to-end delay, average jitter, and QoS violated flows by 51%, 62%, and 28%, respectively.

     

Performance improvement of Deep Learning Models using image augmentation techniques

The major barrier while using deep learning models is lack of large number of images in the training dataset. In fact, there is a need of thousands of images in each image categories based on the complexity of problem. Prior studies have shown that picture augmentation techniques can be used to enhance the number of images in a training dataset artificially. These techniques can aid in improving the overall learning process and performance of a deep learning model. Hence, to address this problem we have proposed three algorithms. Firstly, two image acquisition algorithms have been proposed to systematically obtain real field images for testing and images from public datasets for training a model. Secondly, an algorithm is proposed to describe the procedure how the augmentations can be applied to enhance the datasets. During this study, we have investigated 52 augmentations that can allow enhancing the size of input dataset by improving the quantity of images. To perform the classification process of four maize crop diseases, a new convolutional neural network model is developed and several experiments have been performed to prove its effectiveness. Firstly, two tests were carried out using the original dataset from Kaggle public repository and the augmented dataset. When compared with the original dataset, the model improved by 5.14% with the augmented dataset. Secondly, three experiments carried out to evaluate the performance of proposed augmentation method. Experimental results demonstrated that the proposed approach outperforms the existing three approaches by 27.38%, 3.14%, and 1.34% during the classification process. The proposed IPA augmentation method has been compared with six existing methods: Full Stage Data Augmentation Framework, LeafGAN, Novel Augmentation method based on GAN, Wasserstein Generative Adversarial Network (WGAN), Activation Reconstruction-GAN, and Step-by-Step Data Augmentation Method and experimental results show that performance is better than existing methods by 28.31%, 19.76%, 20.18%, 13.75%, 2.42%, and 12.68% respectively.