Codelivery of Genistein and miRNA-29b to A549 Cells Using Aptamer-Hybrid Nanoparticle Bioconjugates.

This study aimed to evaluate the anti-cancer effect of a combination therapy of miRNA-29b and genistein loaded in mucin-1 (MUC 1)-aptamer functionalized hybrid nanoparticles in non-small cell lung cancer (NSCLC) A549 cell line. Genistein-miRNA-29b-loaded hybrid nanoparticles (GMLHN) was prepared and characterized. Particle size and zeta potential were measured using photon correlation spectroscopy (PCS). Encapsulation efficiency and loading efficiency were determined using HPLC. Preferential internalization of MUC 1-aptamer functionalized GMLHN by A549 cells was evaluated and compared to normal MRC-5 cells. The ability of GMLHN to downregulate targeted oncoproteins Phosphorylated protein kinase, strain AK, Thymoma (Phosphorylated protein kinase B) (pAKT), Phosphorylated phosphoinositide 3-kinase (p-PI3K), DNA (cytosine-5-)-methyltransferase 3 beta (DNMT3B) and Myeloid Cell Leukemia Sequence 1 (MCL 1) was evaluated using western blot, while antiproliferative effect and ability to initiate apoptosis was also assessed in A549 cells. MUC 1-aptamer functionalized GMLHN nanoparticles were prepared. These nanoparticles were preferentially internalized by A549 cells but less so, in MRC-5 cells. pAKT, p-PI3K, DNMT3B and MCL 1 were efficiently downregulated by these nanoparticles without affecting the levels of AKT and PI3K in A549 cells. GMLHN demonstrated a superior antiproliferative effect compared to individual genistein and miRNA-29b-loaded nanoparticles. Results generated were able to demonstrate that genistein-miRNA-29b-loaded hybrid nanoparticles (GMLHN) could be a potential treatment modality for NSCLC because of the ability of the payloads to attack multiple targets

Randomized Assignment of Jobs to Servers in Heterogeneous Clusters of Shared Servers for Low Delay

We consider the job assignment problem in a multi-server system consisting of $N$ parallel processor sharing servers, categorized into $M$ ($\ll N$) different types according to their processing capacity or speed. Jobs of random sizes arrive at the system according to a Poisson process with rate $N \lambda$. Upon each arrival, a small number of servers from each type is sampled uniformly at random. The job is then assigned to one of the sampled servers based on a selection rule. We propose two schemes, each corresponding to a specific selection rule that aims at reducing the mean sojourn time of jobs in the system. We first show that both methods achieve the maximal stability region. We then analyze the system operating under the proposed schemes as $N \to \infty$ which corresponds to the mean field. Our results show that asymptotic independence among servers holds even when $M$ is finite and exchangeability holds only within servers of the same type. We further establish the existence and uniqueness of stationary solution of the mean field and show that the tail distribution of server occupancy decays doubly exponentially for each server type. When the estimates of arrival rates are not available, the proposed schemes offer simpler alternatives to achieving lower mean sojourn time of jobs, as shown by our numerical studies

Downlink Performance of Superimposed Pilots in Massive MIMO systems

In this paper, we investigate the downlink throughput performance of a massive multiple-input multiple-output (MIMO) system that employs superimposed pilots for channel estimation. The component of downlink (DL) interference that results from transmitting data alongside pilots in the uplink (UL) is shown to decrease at a rate proportional to the square root of the number of antennas at the BS. The normalized mean-squared error (NMSE) of the channel estimate is compared with the Bayesian Cram\'{e}r-Rao lower bound that is derived for the system, and the former is also shown to diminish with increasing number of antennas at the base station (BS). Furthermore, we show that staggered pilots are a particular case of superimposed pilots and offer the downlink throughput of superimposed pilots while retaining the UL spectral and energy efficiency of regular pilots. We also extend the framework for designing a hybrid system, consisting of users that transmit either regular or superimposed pilots, to minimize both the UL and DL interference. The improved NMSE and DL rates of the channel estimator based on superimposed pilots are demonstrated by means of simulations.Comment: 28 single-column pages, 6 figures, 1 table, Submitted to IEEE Trans. Wireless Commun. in Aug 2017. Revised Submission in Feb. 201

Joint measurability, steering and entropic uncertainty

The notion of incompatibility of measurements in quantum theory is in stark contrast with the corresponding classical perspective, where all physical observables are jointly measurable. It is of interest to examine if the results of two or more measurements in the quantum scenario can be perceived from a classical point of view or they still exhibit non-classical features. Clearly, commuting observables can be measured jointly using projective measurements and their statistical outcomes can be discerned classically. However, such simple minded association of compatibility of measurements with commutativity turns out to be limited in an extended framework, where the usual notion of sharp projective valued measurements of self adjoint observables gets broadened to include unsharp measurements of generalized observables constituting positive operator valued measures (POVM). There is a surge of research activity recently towards gaining new physical insights on the emergence of classical behavior via joint measurability of unsharp observables. Here, we explore the entropic uncertainty relation for a pair of discrete observables (of Alice's system) when an entangled quantum memory of Bob is restricted to record outcomes of jointly measurable POVMs only. Within the joint measurability regime, the sum of entropies associated with Alice's measurement outcomes - conditioned by the results registered at Bob's end - are constrained to obey an entropic steering inequality. In this case, Bob's non-steerability reflects itself as his inability in predicting the outcomes of Alice's pair of non-commuting observables with better precision, even when they share an entangled state. As a further consequence, the quantum advantage envisaged for the construction of security proofs in key distribution is lost, when Bob's measurements are restricted to the joint measurability regime.Comment: 5 pages, RevTeX, 1 pdf figure, Comments welcom

Sangam Age War Traditions and the Novel Velpari

War has been a part of the lives of the people of the Sangam age. They did not take war merely as a matter of speech, but they treated it in accordance with the rules. This article compares the war with the war traditions of the Sangam age, the war traditions mentioned by Tholkappiyar. And with the novel Velpari, written by S. Venkatesan. If a king wants to wage war against another country, he can wage war only according to the rules. First of all, through spies, they will know the condition of the enemy country and want to capture the wealth of the country, that is, cattle-lifting. Then they will wage war in order to rescue the cattle. The literature highlights the traditions of war, such as the king who won after the end of the war, wearing the flower (albizia lebbeck/woman's tongue). Therefore, although there are innumerable war traditions in the Sangam age, only espionage, cattle-lifting, declaration of war, and flowering have been examined in the article. They have also been examined in terms of comparative criticism and descriptive criticism

Allocation Problems in Ride-Sharing Platforms: Online Matching with Offline Reusable Resources

Bipartite matching markets pair agents on one side of a market with agents, items, or contracts on the opposing side. Prior work addresses online bipartite matching markets, where agents arrive over time and are dynamically matched to a known set of disposable resources. In this paper, we propose a new model, Online Matching with (offline) Reusable Resources under Known Adversarial Distributions (OM-RR-KAD), in which resources on the offline side are reusable instead of disposable; that is, once matched, resources become available again at some point in the future. We show that our model is tractable by presenting an LP-based adaptive algorithm that achieves an online competitive ratio of 1/2 - eps for any given eps greater than 0. We also show that no non-adaptive algorithm can achieve a ratio of 1/2 + o(1) based on the same benchmark LP. Through a data-driven analysis on a massive openly-available dataset, we show our model is robust enough to capture the application of taxi dispatching services and ride-sharing systems. We also present heuristics that perform well in practice.Comment: To appear in AAAI 201