Core promoter short tandem repeats as evolutionary switch codes for primate speciation

Alteration in gene expression levels underlies many of the phenotypic differences across species. Because of their highly mutable nature, proximity to the +1 transcription start site (TSS), and the emerging evidence of functional impact on gene expression, core promoter short tandem repeats (STRs) may be considered an ideal source of variation across species. In a genome-scale analysis of the entire Homo sapiens protein-coding genes, we have previously identified core promoters with at least one STR of ≥6-repeats, with possible selective advantage in this species. In the current study, we performed reverse analysis of the entire Homo sapiens orthologous genes in mouse in the Ensembl database, in order to identify conserved STRs that have shrunk as an evolutionary advantage to humans. Two protocols were used to minimize ascertainment bias. Firstly, two species sharing a more recent ancestor with Homo sapiens (i.e. Pan troglodytes and Gorilla gorilla gorilla) were also included in the study. Secondly, four non-primate species encompassing the major orders across Mammals, including Scandentia, Laurasiatheria, Afrotheria, and Xenarthra were analyzed as out-groups. We introduce STR evolutionary events specifically identical in primates (i.e. Homo sapiens, Pan troglodytes, and Gorilla gorilla gorilla) vs. non-primate out-groups. The average frequency of the identically shared STR motifs across those primates ranged between 0.00005 and 0.06. The identified genes are involved in important evolutionary and developmental processes, such as normal craniofacial development (TFAP2B), regulation of cell shape (PALMD), learning and long-term memory (RGS14), nervous system development (GFRA2), embryonic limb morphogenesis (PBX2), and forebrain development (APAF1). We provide evidence of core promoter STRs as evolutionary switch codes for primate speciation, and the first instance of identity-by-descent for those motifs at the interspecies level. © 2014 Wiley Periodicals, Inc

Gender Detection on Social Networks using Ensemble Deep Learning

Analyzing the ever-increasing volume of posts on social media sites such as Facebook and Twitter requires improved information processing methods for profiling authorship. Document classification is central to this task, but the performance of traditional supervised classifiers has degraded as the volume of social media has increased. This paper addresses this problem in the context of gender detection through ensemble classification that employs multi-model deep learning architectures to generate specialized understanding from different feature spaces

FSL-BM: Fuzzy Supervised Learning with Binary Meta-Feature for Classification

This paper introduces a novel real-time Fuzzy Supervised Learning with Binary Meta-Feature (FSL-BM) for big data classification task. The study of real-time algorithms addresses several major concerns, which are namely: accuracy, memory consumption, and ability to stretch assumptions and time complexity. Attaining a fast computational model providing fuzzy logic and supervised learning is one of the main challenges in the machine learning. In this research paper, we present FSL-BM algorithm as an efficient solution of supervised learning with fuzzy logic processing using binary meta-feature representation using Hamming Distance and Hash function to relax assumptions. While many studies focused on reducing time complexity and increasing accuracy during the last decade, the novel contribution of this proposed solution comes through integration of Hamming Distance, Hash function, binary meta-features, binary classification to provide real time supervised method. Hash Tables (HT) component gives a fast access to existing indices; and therefore, the generation of new indices in a constant time complexity, which supersedes existing fuzzy supervised algorithms with better or comparable results. To summarize, the main contribution of this technique for real-time Fuzzy Supervised Learning is to represent hypothesis through binary input as meta-feature space and creating the Fuzzy Supervised Hash table to train and validate model.Comment: FICC201

On-demand driven dissipation for cavity reset and cooling

We present a superconducting circuit device that provides active, on-demand, tunable dissipation on a target mode of the electromagnetic field. Our device is based on a tunable coupler that can be made lossy when tuned into resonance with a broadband filter mode. When driven parametrically, this coupler induces loss on any mode coupled to it with energy detuning equal to the drive frequency. We demonstrate the use of this device to reset a superconducting qubit's readout cavity after a measurement, resetting it with a characteristic time of under 20 ns. We also demonstrate that the dissipation can be driven constantly and thus suppress thermal photon fluctuations in the cavity, effectively eliminating thermal photon fluctuations as a relevant decoherence channel. Our results demonstrate the utility of our device as a modular tool for environmental engineering and entropy removal in circuit QED.Comment: 12 pages, 6 figure

Evolving evidence on a link between the ZMYM3 exceptionally long GA-STR and human cognition

The human X-linked zinc finger MYM-type protein 3 (ZMYM3) contains the longest GA-STR identified across protein-coding gene 5� UTR sequences, at 32-repeats. This exceptionally long GA-STR is located at a complex string of GA-STRs with a human-specific formula across the complex as follows: (GA)8-(GA)4-(GA)6-(GA)32 (ZMYM3-207 ENST00000373998.5). ZMYM3 was previously reported among the top three genes involved in the progression of late-onset Alzheimer�s disease. Here we sequenced the ZMYM3 GA-STR complex in 750 human male subjects, consisting of late-onset neurocognitive disorder (NCD) as a clinical entity (n = 268) and matched controls (n = 482). We detected strict monomorphism of the GA-STR complex, except of the exceptionally long STR, which was architecturally skewed in respect of allele distribution between the NCD cases and controls F (1, 50) = 12.283; p = 0.001. Moreover, extreme alleles of this STR at 17, 20, 42, and 43 repeats were detected in seven NCD patients and not in the control group (Mid-P exact = 0.0003). A number of these alleles overlapped with alleles previously found in schizophrenia and bipolar disorder patients. In conclusion, we propose selective advantage for the exceptional length of the ZMYM3 GA-STR in human, and its link to a spectrum of diseases in which major cognition impairment is a predominant phenotype. © 2020, The Author(s)

Ionic liquids at electrified interfaces

Until recently, “room-temperature” (<100–150 °C) liquid-state electrochemistry was mostly electrochemistry of diluted electrolytes(1)–(4) where dissolved salt ions were surrounded by a considerable amount of solvent molecules. Highly concentrated liquid electrolytes were mostly considered in the narrow (albeit important) niche of high-temperature electrochemistry of molten inorganic salts(5-9) and in the even narrower niche of “first-generation” room temperature ionic liquids, RTILs (such as chloro-aluminates and alkylammonium nitrates).(10-14) The situation has changed dramatically in the 2000s after the discovery of new moisture- and temperature-stable RTILs.(15, 16) These days, the “later generation” RTILs attracted wide attention within the electrochemical community.(17-31) Indeed, RTILs, as a class of compounds, possess a unique combination of properties (high charge density, electrochemical stability, low/negligible volatility, tunable polarity, etc.) that make them very attractive substances from fundamental and application points of view.(32-38) Most importantly, they can mix with each other in “cocktails” of one’s choice to acquire the desired properties (e.g., wider temperature range of the liquid phase(39, 40)) and can serve as almost “universal” solvents.(37, 41, 42) It is worth noting here one of the advantages of RTILs as compared to their high-temperature molten salt (HTMS)(43) “sister-systems”.(44) In RTILs the dissolved molecules are not imbedded in a harsh high temperature environment which could be destructive for many classes of fragile (organic) molecules

Bayesian estimation of seismic hazards in Iran

Seismic hazard assessment is a basic tool for rational planning and designing in areas of different seismic activity. The Bayesian probability estimation was applied in this study to assess seismic hazard. The estimation procedure provides a posterior probability distribution that integrates prior estimates based on the knowledge of the process, and the likelihood of occurrence based on historical data. The Bayesian approach was applied to calculate the probability that a certain cut-off magnitude would be exceeded at certain time intervals in different regions of Iran. The results for the cut-off magnitude of 6.5 indicate that the highest probability of seismic hazard exists in the Alborz, Kopeh-Dagh, Bandar-Abas, Kerman, and Zagros regions. The seismic hazard is lowest for the Esfahan&ndash;Sirgan region, the Arabian Platform, the Persian Gulf, and Kavir in Central Iran. The comparison between the Bayesian results and the seismotectonic models of Iran reveals that it is possible to partition the spatially distributed epicenters of earthquake events into different regions. In general, these regional divisions agree with previously proposed seismotectonic provinces of Iran