ENROUTE: An Entropy Aware Routing Scheme for Information-Centric Networks (ICN)

With the exponential growth of end users and web data, the internet is undergoing the change of paradigm from a user-centric model to a content-centric one, popularly known as information-centric networks (ICN). Current ICN research evolves around three key-issues namely (i) content request searching, (ii) content routing, and (iii) in-network caching scheme to deliver the requested content to the end user. This would improve the user experience to obtain requested content because it lowers the download delay and provides higher throughput. Existing researches have mainly focused on on-path congestion or expected delivery time of a content to determine the optimized path towards custodian. However, it ignores the cumulative effect of the link-state parameters and the state of the cache, and consequently it leads to degrade the delay performance. In order to overcome this shortfall, we consider both the congestion of a link and the state of on-path caches to determine the best possible routes. We introduce a generic term entropy to quantify the effects of link congestion and state of on-path caches. Thereafter, we develop a novel entropy dependent algorithm namely ENROUTE for searching of content request triggered by any user, routing of this content, and caching for the delivery this requested content to the user. The entropy value of an intra-domain node indicates how many popular contents are already cached in the node, which, in turn, signifies the degree of enrichment of that node with the popular contents. On the other hand, the entropy for a link indicates how much the link is congested with the traversal of contents. In order to have reduced delay, we enhance the entropy of caches in nodes, and also use path with low entropy for downloading contents. We evaluate the performance of our proposed ENROUTE algorithm against state-of-the-art schemes for various network parameters and observe an improvement of 29–52% in delay, 12–39% in hit rate, and 4–39% in throughput.

     

All‐Organic Dual Spin Valves with Well‐Resolved Four Resistive‐States

The formation of all‐organic dual spin valves (DSVs) with three organic spin‐selective layers, that is, spin‐injection, spin‐detection, and an additional spin‐filtering layer at the intermediate, is reported. As spin‐selective layers, manganese‐ and cobalt phthalocyanines, which are well‐known single‐molecule magnets, are used in their immobilized forms, so that all‐organic DSVs can be prefabricated for characterization. The three spin‐selective layers have provided four configurations with at most two spin‐flip interfaces enforcing spin‐flipping at the two nonmagnetic organic spacer layers, for which copper phthalocyanine is used. Since a couple of the four configurations have exhibited similar resistivities, the degeneracy in the resistive‐states is broken through asymmetric spin‐injection and spin‐detection layers and also through asymmetric thickness of the nonmagnetic spacer layers. When both the spin‐flip interfaces are made operative independently, a 2‐bit logic with four distinct resistive states can be achieved.     

Partition oriented frame based fair scheduler

Proportionate fair schedulers provide an effective methodology for scheduling recurrent real-time tasks on multiprocessors. However, a drawback in these schedulers is that they ignore a task’s affinity towards the processor where it was executed last, causing frequent inter-processor task migrations which ultimately results in increased execution times. This paper presents Partition Oriented Frame Based Fair Scheduler (POFBFS), an efficient proportional fair scheduler for periodic firm and soft real-time tasks that ensures a bounded number of task migrations. Experimental results reveal that POFBFS can achieve 3 to 100 times reduction in the number of migrations suffered with respect to the General-ERfair algorithm (for a set of 25 to 100 tasks running on 2 to 8 processors) while simultaneously maintaining high fairness accuracy.     

Time evolution of entanglement and bistability of two coupled quantum dots in a driven cavity

Abstract

The time evolution of entanglement between two quantum dots (QDs) trapped inside a cavity driven by a coherent quantized field is studied. In the presence of dissipation, entanglement shows many interesting features such as sudden death and revival, and finite steady state value after sudden death. We also investigate dependence of entanglement on dot variables and its relation to bistability. It is found that entanglement vanishes when the cavity field intensity approaches the upper branch of the bistability curve. When the cavity is driven by a modulated field in the presence of dissipation, it can periodically generate entanglement, which is much larger than the maximum value attained in the steady-state for this system but the dots are never fully entangled.     

Overcoming Radiation Resistance in Gliomas by Targeting Metabolism and DNA Repair Pathways

Gliomas represent a wide spectrum of brain tumors characterized by their high invasiveness, resistance to chemoradiotherapy, and both intratumoral and intertumoral heterogeneity. Recent advances in transomics studies revealed that enormous abnormalities exist in different biological layers of glioma cells, which include genetic/epigenetic alterations, RNA expressions, protein expression/modifications, and metabolic pathways, which provide opportunities for development of novel targeted therapeutic agents for gliomas. Metabolic reprogramming is one of the hallmarks of cancer cells, as well as one of the oldest fields in cancer biology research. Altered cancer cell metabolism not only provides energy and metabolites to support tumor growth, but also mediates the resistance of tumor cells to antitumor therapies. The interactions between cancer metabolism and DNA repair pathways, and the enhancement of radiotherapy sensitivity and assessment of radiation response by modulation of glioma metabolism are discussed herein.     

Soluble activated charcoal

Reduction of activated charcoal by lithium in liquid ammonia yields charcoal salts that can be reacted with dodecyl iodide to yield soluble dodecylated activated charcoal. Atomic force microscopy images reveal a heterogeneous size distribution of nearly spherical nanoparticles. High-resolution transmission electron microscopy images show a layered microcrystalline arrangement that becomes separated to form mostly single layered disordered structures after dodecylation. A ¹H-¹³C cross polarization magic angle spinning spectrum of the charcoal revealed a broad, featureless signal from sp² carbons and a much weaker broad signal from aliphatic carbons.     

N-ocular volume holographic imaging

Volume holographic imaging utilizes Bragg selectivity to optically slice the object space of the imaging system and measure four- (three spatial and one spectral) dimensional object information. The N-ocular version of this method combines multiple-volume holographic sensors and digital postprocessing to yield high-resolution three-dimensional images for broadband objects located at long working distances. We discuss the physical properties of volume holography pertinent to imaging performance and describe two computational algorithms for image inversion based on filtered backprojection and least-squares optimization.     

Higher order direct model reference adaptive control with generic uniform ultimate boundedness

This paper proposes a new higher order model reference adaptive control (HO-MRAC) approach following direct adaptive control philosophy, which estimates unknown time-varying parameters. This approach leads to a Lyapunov based conventional MRAC update law, augmented by an observer type parameter predictor dynamics. The predictor dynamics are composed of a stable known part, a feedback of the parameter error and unknown higher order parameters, which are updated using a Lyapunov based adaptive design. So, this HO-MRAC can cope with rapidly changing parameters, due to estimation of their time derivatives. Moreover, for stability analysis, a Lyapunov based generic ultimate boundedness theorem is presented, which allows for a computation of separate bounds for each state vector partition. Furthermore, this theorem formulates the explicit specification of transient and ultimate bounds, reaching time on the ultimate bounds and a set of admissible initial conditions. Two challenging illustrative examples demonstrate the effectiveness of the proposed approach.     

A design fix to supervisory control for fault-tolerant scheduling of real-time multiprocessor systems with aperiodic tasks

In the article ‘Supervisory control for fault-tolerant scheduling of real-time multiprocessor systems with aperiodic tasks’, Park and Cho presented a systematic way of computing a largest fault-tolerant and schedulable language that provides information on whether the scheduler (i.e., supervisor) should accept or reject a newly arrived aperiodic task. The computation of such a language is mainly dependent on the task execution model presented in their paper. However, the task execution model is unable to capture the situation when the fault of a processor occurs even before the task has arrived. Consequently, a task execution model that does not capture this fact may possibly be assigned for execution on a faulty processor. This problem has been illustrated with an appropriate example. Then, the task execution model of Park and Cho has been modified to strengthen the requirement that none of the tasks are assigned for execution on a faulty processor.