4,938 research outputs found

    Nonadaptive Amino Acid Convergence Rates Decrease over Time.

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    Convergence is a central concept in evolutionary studies because it provides strong evidence for adaptation. It also provides information about the nature of the fitness landscape and the repeatability of evolution, and can mislead phylogenetic inference. To understand the role of adaptive convergence, we need to understand the patterns of nonadaptive convergence. Here, we consider the relationship between nonadaptive convergence and divergence in mitochondrial and model proteins. Surprisingly, nonadaptive convergence is much more common than expected in closely related organisms, falling off as organisms diverge. The extent of the convergent drop-off in mitochondrial proteins is well predicted by epistatic or coevolutionary effects in our "evolutionary Stokes shift" models and poorly predicted by conventional evolutionary models. Convergence probabilities decrease dramatically if the ancestral amino acids of branches being compared have diverged, but also drop slowly over evolutionary time even if the ancestral amino acids have not substituted. Convergence probabilities drop-off rapidly for quickly evolving sites, but much more slowly for slowly evolving sites. Furthermore, once sites have diverged their convergence probabilities are extremely low and indistinguishable from convergence levels at randomized sites. These results indicate that we cannot assume that excessive convergence early on is necessarily adaptive. This new understanding should help us to better discriminate adaptive from nonadaptive convergence and develop more relevant evolutionary models with improved validity for phylogenetic inference

    Sentimental Analysis of Twitter Data using Classifier Algorithms

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    Microblogging has become a daily routine for most of the people in this world. With the help of Microblogging people get opinions about several things going on, not only around the nation but also worldwide. Twitter is one such online social networking website where people can post their views regarding something. It is a huge platform having over 316 Million users registered from all over the world. It enables users to send and read short messages with over 140 characters for compatibility with SMS messaging. A good sentimental analysis of data of this huge platform can lead to achieve many new applications like – Movie reviews, Product reviews, Spam detection, Knowing consumer needs, etc. In this paper, we have devised a new algorithm with which the above needs can be achieved. Our algorithm uses three specific techniques for sentimental analysis and can be called a hybrid algorithm – (1) Hash Tag Classification for topic modeling; (2) NaΓ―ve Bayes Classifier Algorithm for polarity classification; (3) Emoticon Analysis for Neutral polar data. These techniques individually have some limitations for sentimental analysis

    Lessons learned from the development and implementation of a patient-reported outcome and experience measure (POEM) in an Australian glaucoma practice.

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    BACKGROUND: A patient's perception of how their glaucoma is managed will influence both adherence to their medication and outcome measures such as quality of life. METHODS: Prospective consecutive study using a Glaucoma Patient-reported Outcome and Experience Measure (POEM) modified for an Australian ophthalmic private clinical practice setting. The Australian Glaucoma POEM consists of eight items related to the patient's understanding of the diagnosis and management, acceptability of the treatment, whether they feel their glaucoma is getting worse, interfering with their daily life and concerns regarding loss of vision as well as addressing whether they feel safe under the care of their glaucoma team and how well their care is organised. RESULTS: Two hundred and two patients (M:F 91:111) participated in the study. Mean ± standard deviation for subject age was 69 ± 13 years. Patient's overall perception of their treatment and outcome was favourable. Younger patients felt their glaucoma interfered more with their daily lives and were more worried about losing vision from glaucoma. The greater the number of medications in use, the more they felt their glaucoma was getting worse and that glaucoma interfered with their daily lives. With all other variables accounted for by the multivariate linear model, female patients more strongly agreed that they understood their glaucoma diagnosis and glaucoma management. The patients with a severe visual defect in their worse eye, reported a greater perceived understanding of their glaucoma diagnosis and management and that they felt that glaucoma had a greater interference on their daily life. They were also more concerned about losing vision from glaucoma than their fellow glaucoma patients with less severe or no visual field deficit in the worse eye. CONCLUSIONS: The modified POEM demonstrates potential to capture the concerns of a practice's glaucoma cohort with a view to enhancing the quality of glaucoma care delivered

    Production of bioethanol through enzymatic hydrolysis of potato

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    Due to gradual decrease in petroleum resources and impacts of these wastes on the environment, there is a need to utilize the wastes of potatoes to get wealth out of wastes and clean the environment. In this study, potato wastes were investigated as source of bioethanol. 100 g potato powder was mixed with 1 L distilled water in two separate beakers to form potato slurry. Bioethanol production was investigated using effect of pH, temperature and mixture of digesting enzymes after scarification and fermentation. The results show that significant (p<0.05) bioethanol was produced at 35Β°C and at pH 5.5. This investigation also reveals that mixture of enzymes significantly enhanced (p<0.05) bioethanol production compared to non treated mixture. Maximum bioethanol productions were due to the presence of sugar in potatoes.Key words: Bioethanol, potato, ph, temperature, liquefaction

    SLEPX: An Efficient Lightweight Cipher for Visual Protection of Scalable HEVC Extension

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    This paper proposes a lightweight cipher scheme aimed at the scalable extension of the High Efficiency Video Coding (HEVC) codec, referred to as the Scalable HEVC (SHVC) standard. This stream cipher, Symmetric Cipher for Lightweight Encryption based on Permutation and EXlusive OR (SLEPX), applies Selective Encryption (SE) over suitable coding syntax elements in the SHVC layers. This is achieved minimal computational complexity and delay. The algorithm also conserves most SHVC functionalities, i.e. preservation of bit-length, decoder format-compliance, and error resilience. For comparative analysis, results were taken and compared with other state-of-art ciphers i.e. Exclusive-OR (XOR) and the Advanced Encryption Standard (AES). The performance of SLEPX is also compared with existing video SE solutions to confirm the efficiency of the adopted scheme. The experimental results demonstrate that SLEPX is as secure as AES in terms of visual protection, while computationally efficient comparable with a basic XOR cipher. Visual quality assessment, security analysis and extensive cryptanalysis (based on numerical values of selected binstrings) also showed the effectiveness of SLEPX’s visual protection scheme for SHVC compared to previously-employed cryptographic technique

    Combinatorial Roles of Heparan Sulfate Proteoglycans and Heparan Sulfates in Caenorhabditis elegans Neural Development

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    Heparan sulfate proteoglycans (HSPGs) play critical roles in the development and adult physiology of all metazoan organisms. Most of the known molecular interactions of HSPGs are attributed to the structurally highly complex heparan sulfate (HS) glycans. However, whether a specific HSPG (such as syndecan) contains HS modifications that differ from another HSPG (such as glypican) has remained largely unresolved. Here, a neural model in C. elegans is used to demonstrate for the first time the relationship between specific HSPGs and HS modifications in a defined biological process in vivo. HSPGs are critical for the migration of hermaphrodite specific neurons (HSNs) as genetic elimination of multiple HSPGs leads to 80% defect of HSN migration. The effects of genetic elimination of HSPGs are additive, suggesting that multiple HSPGs, present in the migrating neuron and in the matrix, act in parallel to support neuron migration. Genetic analyses suggest that syndecan/sdn-1 and HS 6-O-sulfotransferase, hst-6, function in a linear signaling pathway and glypican/lon-2 and HS 2-O-sulfotransferase, hst-2, function together in a pathway that is parallel to sdn-1 and hst-6. These results suggest core protein specific HS modifications that are critical for HSN migration. In C. elegans, the core protein specificity of distinct HS modifications may be in part regulated at the level of tissue specific expression of genes encoding for HSPGs and HS modifying enzymes. Genetic analysis reveals that there is a delicate balance of HS modifications and eliminating one HS modifying enzyme in a compromised genetic background leads to significant changes in the overall phenotype. These findings are of importance with the view of HS as a critical regulator of cell signaling in normal development and disease

    Metabolomics to unveil and understand phenotypic diversity between pathogen populations

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    Visceral leishmaniasis is caused by a parasite called Leishmania donovani, which every year infects about half a million people and claims several thousand lives. Existing treatments are now becoming less effective due to the emergence of drug resistance. Improving our understanding of the mechanisms used by the parasite to adapt to drugs and achieve resistance is crucial for developing future treatment strategies. Unfortunately, the biological mechanism whereby Leishmania acquires drug resistance is poorly understood. Recent years have brought new technologies with the potential to increase greatly our understanding of drug resistance mechanisms. The latest mass spectrometry techniques allow the metabolome of parasites to be studied rapidly and in great detail. We have applied this approach to determine the metabolome of drug-sensitive and drug-resistant parasites isolated from patients with leishmaniasis. The data show that there are wholesale differences between the isolates and that the membrane composition has been drastically modified in drug-resistant parasites compared with drug-sensitive parasites. Our findings demonstrate that untargeted metabolomics has great potential to identify major metabolic differences between closely related parasite strains and thus should find many applications in distinguishing parasite phenotypes of clinical relevance

    Hidden Orbital Order in URu2Si2URu_{2}Si_{2}

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    When matter is cooled from high temperatures, collective instabilities develop amongst its constituent particles that lead to new kinds of order. An anomaly in the specific heat is a classic signature of this phenomenon. Usually the associated order is easily identified, but sometimes its nature remains elusive. The heavy fermion metal URu2Si2URu_2Si_2 is one such example, where the order responsible for the sharp specific heat anomaly at T0=17KT_0=17 K has remained unidentified despite more than seventeen years of effort. In URu2Si2URu_{2}Si_{2}, the coexistence of large electron-electron repulsion and antiferromagnetic fluctuations in URu2Si2URu_2Si_2 leads to an almost incompressible heavy electron fluid, where anisotropically paired quasiparticle states are energetically favored. In this paper we use these insights to develop a detailed proposal for the hidden order in URu2Si2URu_2Si_2. We show that incommensurate orbital antiferromagnetism, associated with circulating currents between the uranium ions, can account for the local fields and entropy loss observed at the 17K17 K transition; furthermore we make detailed predictions for neutron scattering measurements
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