762 research outputs found

    PHP59 PHARMACY BENEFIT INTEGRATION AND ADHERENCE TO EVIDENCE-BASED MEDICINE IN A COMMERCIALLY-INSURED POPULATION

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    A novel spectral-efficient resource allocation approach for NOMA-based full-duplex systems

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    © 2019 IEEE. This paper investigates the coexistence of non- orthogonal multiple access (NOMA) and full-duplex (FD), where the NOMA successive interference cancellation technique is applied simultaneously to both uplink (UL) and downlink (DL) transmissions in the same time-frequency resource block. Specifically, we jointly optimize the user association (UA) and power control to maximize the overall sum rate, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize the UL users' decoding order and the DL users' clustering, which results in a mixed-integer non- convex problem. For solving this problem, we first relax the binary variables to be continuous, and then propose a low-complexity design based on the combination of the inner convex approximation framework and the penalty method. Numerical results show that the proposed algorithm significantly outperforms the conventional FD-based schemes, FD-NOMA and its half-duplex counterpart with random UA

    Joint Power Control and User Association for NOMA-Based Full-Duplex Systems

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    © 1972-2012 IEEE. This paper investigates the coexistence of non-orthogonal multiple access (NOMA) and full-duplex (FD) to improve both spectral efficiency (SE) and user fairness. In such a scenario, NOMA based on the successive interference cancellation technique is simultaneously applied to both uplink (UL) and downlink (DL) transmissions in an FD system. We consider the problem of jointly optimizing user association (UA) and power control to maximize the overall SE, subject to user-specific quality-of-service and total transmit power constraints. To be spectrally-efficient, we introduce the tensor model to optimize UL users' decoding order and DL users' clustering, which results in a mixed-integer non-convex problem. For practically appealing applications, we first relax the binary variables and then propose two low-complexity designs. In the first design, the continuous relaxation problem is solved using the inner convex approximation framework. Next, we additionally introduce the penalty method to further accelerate the performance of the former design. For a benchmark, we develop an optimal solution based on brute-force search (BFS) over all possible cases of UAs. It is demonstrated in numerical results that the proposed algorithms outperform the conventional FD-based schemes and its half-duplex counterpart, as well as yield data rates close to those obtained by BFS-based algorithm

    Effects of operational disturbance and subsequent recovery process on microbial community during a pilot-scale anaerobic co-digestion

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    © 2019 This study investigated changes in microbial community structure and composition in response to operational disturbance and subsequent process recovery by inoculum addition. Amplicon sequencing of 16S rRNA and mcrA marker genes on the Illumina Miseq platform was used for microbial community analysis. The results show that imbalance among core microbial groups caused volatile fatty acid accumulation and subsequent deteriorated biogas production (decreased by 45% of daily volume) and methane content (57% of the total abundance) and reduction of acetogenic and methanogenic microbes (they accounted for <9% and <3% of the total abundance, respectively). Acetogens and methanogens were replenished by inoculum addition to recover digester performance. Although digester performances were similar in stable (prior to disturbance) and post recovery phases, the microbial community did not return to the original state, suggesting the existence of functional redundancy in the community

    Time Series Analysis for Encrypted Traffic Classification: A Deep Learning Approach

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    © 2018 IEEE. We develop a novel time series feature extraction technique to address the encrypted traffic/application classification problem. The proposed method consists of two main steps. First, we propose a feature engineering technique to extract significant attributes of the encrypted network traffic behavior by analyzing the time series of receiving packets. In the second step, we develop a deep learning-based technique to exploit the correlation of time series data samples of the encrypted network applications. To evaluate the efficiency of the proposed solution on the encrypted traffic classification problem, we carry out intensive experiments on a raw network traffic dataset, namely VPN-nonVPN, with three conventional classifier metrics including Precision, Recall, and F1 score. The experimental results demonstrate that our proposed approach can significantly improve the performance in identifying encrypted application traffic in terms of accuracy and computation efficiency

    A systematic review and meta-analyses of pregnancy and fetal outcomes in women with multiple sclerosis: a contribution from the IMI2 ConcePTION project.

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    Neurologists managing women with Multiple Sclerosis (MS) need information about the safety of disease modifying drugs (DMDs) during pregnancy. However, this knowledge is limited. The present study aims to summarize previous studies by performing a systematic review and meta-analyses. The terms "multiple sclerosis" combined with DMDs of interest and a broad profile for pregnancy terms were used to search Embase and Medline databases to identify relevant studies published from January 2000 to July 2019.1260 studies were identified and ten studies met our inclusion criteria. Pooled risk ratios (RR) of pregnancy and birth outcomes in pregnancies exposed to DMDs compared to those not exposed were calculated using a random effects model. For spontaneous abortion RR = 1.14, 95% CI 0.99-1.32, for preterm births RR = 0.93, 95% CI 0.72-1.21 and for major congenital malformations RR = 0.86, 95% CI 0.47-1.56. The most common major congenital malformations reported in MS patients exposed to MS drugs were atrial septal defect (ASD) (N = 4), polydactyly (N = 4) and club foot (N = 3), which are among the most prevalent birth defects observed in the general population. In conclusion, interferons, glatiramer acetate or natalizumab, do not appear to increase the risk for spontaneous abortions, pre-term birth or major congenital malformations. There were very few patients included that were exposed to fingolimod, azathioprine and rituximab; therefore, these results cannot be generalized across drugs. Future studies including internal comparators are needed to enable treating physicians and their patients to decide on the best treatment options

    Detection and monitoring of cancers with biosensors in Vietnam

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    Biosensors are able to provide fast, accurate and reliable detec-tions and monitoring of cancer cells, as well as to determine the effectiveness of anticancer chemotherapy agents in cancer treatments. These have attracted a great attention of research communities, especially in the capabilities of detecting the path-ogens, viruses and cancer cells in narrow scale that the conven-tional apparatus and techniques do not have. This paper pre-sents technologies and applications of biosensors for detections of cancer cells and related diseases, with the focus on the cur-rent research and technology development about biosensors in Vietnam, a typical developing country with a very high number of patients diagnosed with cancers in recent years, but having a very low cancer survival rate. The role of biosensors in early detections of diseases, cancer screening, diagnosis and treat-ment, is more and more important; especially it is estimated that by 2020, 60-70% new cases of cancers and nearly 70% of cancer deaths will be in economically disadvantaged countries. The paper is also aimed to open channels for the potential R&D collaborations with partners in Vietnam in the areas of innovative design and development of biosensors in particular and medical technology devices in general

    On the complexity of the Saccharomyces bayanus taxon: hybridization and potential hybrid speciation

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    Although the genus Saccharomyces has been thoroughly studied, some species in the genus has not yet been accurately resolved; an example is S. bayanus, a taxon that includes genetically diverse lineages of pure and hybrid strains. This diversity makes the assignation and classification of strains belonging to this species unclear and controversial. They have been subdivided by some authors into two varieties (bayanus and uvarum), which have been raised to the species level by others. In this work, we evaluate the complexity of 46 different strains included in the S. bayanus taxon by means of PCR-RFLP analysis and by sequencing of 34 gene regions and one mitochondrial gene. Using the sequence data, and based on the S. bayanus var. bayanus reference strain NBRC 1948, a hypothetical pure S. bayanus was reconstructed for these genes that showed alleles with similarity values lower than 97% with the S. bayanus var. uvarum strain CBS 7001, and of 99¿100% with the non S. cerevisiae portion in S. pastorianus Weihenstephan 34/70 and with the new species S. eubayanus. Among the S. bayanus strains under study, different levels of homozygosity, hybridization and introgression were found; however, no pure S. bayanus var. bayanus strain was identified. These S. bayanus hybrids can be classified into two types: homozygous (type I) and heterozygous hybrids (type II), indicating that they have been originated by different hybridization processes. Therefore, a putative evolutionary scenario involving two different hybridization events between a S. bayanus var. uvarum and unknown European S. eubayanus-like strains can be postulated to explain the genomic diversity observed in our S. bayanus var. bayanus strains

    Salmonella typhimurium Suppresses Tumor Growth via the Pro-Inflammatory Cytokine Interleukin-1 beta

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    Although strains of attenuated Salmonella typhimurium and wild-type Escherichia coli show similar tumor-targeting capacities, only S. typhimurium significantly suppresses tumor growth in mice. The aim of the present study was to examine bacteria-mediated immune responses by conducting comparative analyses of the cytokine profiles and immune cell populations within tumor tissues colonized by E. coli or attenuated Salmonellae. CT26 tumor-bearing mice were treated with two different bacterial strains: S. typhimurium defective in ppGpp synthesis (Delta ppGpp Salmonellae) or wild-type E. coli MG1655. Cytokine profiles and immune cell populations in tumor tissue colonized by these two bacterial strains were examined at two time points based on the pattern of tumor growth after Delta ppGpp Salmonellae treatment: 1) when tumor growth was suppressed (&apos;suppression stage&apos;) and 2) when they began to re-grow (&apos;re-growing stage&apos;). The levels of IL-1 beta and TNF-alpha were markedly increased in tumors colonized by Delta ppGpp Salmonellae. This increase was associated with tumor regression; the levels of both IL-1 beta and TNF-alpha returned to normal level when the tumors started to re-grow. To identify the immune cells primarily responsible for Salmonellae-mediated tumor suppression, we examined the major cell types that produce IL-1 beta and TNF-alpha. We found that macrophages and dendritic cells were the main producers of TNF-alpha and IL-1 beta. Inhibiting IL-1 beta production in Salmonellae-treated mice restored tumor growth, whereas tumor growth was suppressed for longer by local administration of recombinant IL-1 beta or TNF-alpha in conjunction with Salmonella therapy. These findings suggested that IL-1 beta and TNF-alpha play important roles in Salmonella-mediated cancer therapy. A better understanding of host immune responses in Salmonella therapy may increase the success of a given drug, particularly when various strategies are combined with bacteriotherapy.111715Ysciescopu
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