Miracle-dz/UniFAR-FTUs huggingface dataset:
gbtools: Interactive Visualization of Metagenome Bins in R

Improvements in DNA sequencing technology have increased the amount and quality of sequences that can be obtained from metagenomic samples, making it practical to extract individual microbial genomes from metagenomic assemblies (“binning”). However, while many tools and methods exist for unsupervised binning with various statistical algorithms, there are few options for visualizing the results, even though visualization is vital to exploratory data analysis. We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other. We illustrate some of the functions available in gbtools with two examples: the metagenome of Olavius algarvensis, a marine oligochaete worm that has up to five bacterial symbionts, and the metagenome of a synthetic mock community comprising 64 bacterial and archaeal strains. We show how instances of poor automated binning, sequencer GC% bias, and variation between samples can be quickly diagnosed by visualization, and demonstrate how the results from different binning tools can be combined and refined to yield manually curated bins with higher completeness. gbtools is open-source and written in R. The software package, documentation, and example data are available freely online at https://github.com/kbseah/genome-bin-tools.
Interleukin-1 Receptor-Associated Kinase-3 Is a Key Inhibitor of Inflammation in Obesity and Metabolic Syndrome

Background Visceral obesity is associated with the rising incidence of type 2 diabetes and metabolic syndrome. Low-grade chronic inflammation and oxidative stress synergize in obesity and obesity-induced disorders. Objective We searched a cluster of molecules that support interactions between these stress conditions in monocytes. Methods RNA expressions in blood monocytes of two independent cohorts comprising 21 and 102 obese persons and 46 age-matched controls were determined by microarray and independently validated by quantitative RT-PCR analysis. The effect of three-month weight loss after bariatric surgery was determined. The effect of RNA silencing on inflammation and oxidative stress was studied in human monocytic THP-1 cells. Results Interleukin-1 receptor-associated kinase-3 (IRAK3), key inhibitor of IRAK/NFκB-mediated chronic inflammation, is downregulated in monocytes of obese persons. Low IRAK3 was associated with high superoxide dismutase-2 (SOD2), a marker of mitochondrial oxidative stress. A comparable expression profile was also detected in visceral adipose tissue of the same obese subjects. Low IRAK3 and high SOD2 was associated with a high prevalence of metabolic syndrome (odds ratio: 9.3; sensitivity: 91%; specificity: 77%). By comparison, the odds ratio of high-sensitivity C-reactive protein, a widely used marker of systemic inflammation, was 4.3 (sensitivity: 69%; specificity: 66%). Weight loss was associated with an increase in IRAK3 and a decrease in SOD2, in association with a lowering of systemic inflammation and a decreasing number of metabolic syndrome components. We identified the increase in reactive oxygen species in combination with obesity-associated low adiponectin and high glucose and interleukin-6 as cause of the decrease in IRAK3 in THP-1 cells in vitro. Conclusion IRAK3 is a key inhibitor of inflammation in association with obesity and metabolic syndrome. Our data warrant further evaluation of IRAK3 as a diagnostic and prognostic marker, and as a target for intervention.
MaM : Multiple alignment Manipulator

Summary:MaM is a software tool that processes and manipulates multiple alignments of genomic sequence. MaM computes the exact location of common repeat elements, exons, and unique regions within aligned genomics sequences using a variety of user identified programs, databases, and/or tables. The program can extract subalignments, corresponding to these various regions of DNA to be analyzed independently or in conjunction with other elements of genomic DNA. Graphical displays further allow an assessment of sequence variation throughout these different regions of the aligned sequence, providing separate displays for their repeat, non-repeat and coding portions of genomic DNA. The program should facilitate the phylogenetic analysis and processing of different portions of genomic sequence as part of large-scale sequencing efforts. Availability: MaM is freely available for non-commercial use at http://genomics.cwru. edu/MAM.html
A Non-parametric Model for Partial Volume Segmentation of MR Images

We consider the problem of fitting the intensity distribution of an MR image using probability mass functions (PMFs) of pure and partial tissue classes. To do this, we adapt a recently proposed PMF estimation method for critically or over sampled signals. This enables us to estimate pure tissue PMFs directly from the image. Unlike most previous methods, we make no assumptions about the parametric form of the pure tissue PMFs (e.g. that they follow Gaussian distributions). We demonstrate the applicability of the algorithm to formulate partial volume segmentation in a Bayesian framework, where the a priori PMF of pure and partial tissue classes is estimated using an inequality constrained least squares method. The utility of the algorithm is shown on simulated and real data, comprised of both brain and non-brain MR images.
The crystal structure of the Rv0301‐Rv0300 VapBC‐3 toxin—antitoxin complex from M. tuberculosis reveals a Mg2+ ion in the active site and a putative RNA‐binding site

VapBC pairs account for 45 out of 88 identified toxin‐antitoxin (TA) pairs in the Mycobacterium tuberculosis (Mtb) H37Rv genome. A working model suggests that under times of stress, antitoxin molecules are degraded, releasing the toxins to slow the metabolism of the cell, which in the case of VapC toxins is via their RNase activity. Otherwise the TA pairs remain bound to their promoters, autoinhibiting transcription. The crystal structure of Rv0301‐Rv0300, an Mtb VapBC TA complex determined at 1.49 Å resolution, suggests a mechanism for these three functions: RNase activity, its inhibition by antitoxin, and its ability to bind promoter DNA. The Rv0301 toxin consists of a core of five parallel beta strands flanked by alpha helices. Three proximal aspartates coordinate a Mg2+ ion forming the putative RNase active site. The Rv0300 antitoxin monomer is extended in structure, consisting of an N‐terminal beta strand followed by four helices. The last two helices wrap around the toxin and terminate near the putative RNase active site, but with different conformations. In one conformation, the C‐terminal arginine interferes with Mg2+ ion coordination, suggesting a mechanism by which the antitoxin can inhibit toxin activity. At the N‐terminus of the antitoxin, two pairs of Ribbon‐Helix‐Helix (RHH) motifs are related by crystallographic twofold symmetry. The resulting hetero‐octameric complex is similar to the FitAB system, but the two RHH motifs are about 30 Å closer together in the Rv0301‐Rv0300 complex, suggesting either a different span of the DNA recognition sequence or a conformational change.
A cascade of warming impacts brings bluefin tuna to Greenland waters

Rising ocean temperatures are causing marine fish species to shift spatial distributions and ranges, and are altering predator‐prey dynamics in food webs. Most documented cases of species shifts so far involve relatively small species at lower trophic levels, and consider individual species in ecological isolation from others. Here, we show that a large highly migratory top predator fish species has entered a high latitude subpolar area beyond its usual range. Bluefin tuna, Thunnus thynnus Linnaeus 1758, were captured in waters east of Greenland (65°N) in August 2012 during exploratory fishing for Atlantic mackerel, Scomber scombrus Linnaeus 1758. The bluefin tuna were captured in a single net‐haul in 9–11 °C water together with 6 tonnes of mackerel, which is a preferred prey species and itself a new immigrant to the area. Regional temperatures in August 2012 were historically high and contributed to a warming trend since 1985, when temperatures began to rise. The presence of bluefin tuna in this region is likely due to a combination of warm temperatures that are physiologically more tolerable and immigration of an important prey species to the region. We conclude that a cascade of climate change impacts is restructuring the food web in east Greenland waters.
Preprocessing techniques of facial image with Median and Gabor filters

Image Preprocessing is an essential factor for any Face image, when processing it for research purpose, The need for Preprocessing is due to its variation in Lightening condition, differences in Pose, Head orientation and Expressions because the quality of an Image depend on the effectiveness of capture device like CCTV, Webcams etc. The common Preprocessing involves Color Normalization, Noise Reduction, Edge Detection and Histogram Equalization. The aim of Preprocessing is to improve the quality of the Image and to enhance the Image features for further processing. In this paper Median filter is used for Color Normalization and Noise Reduction. Gabor filter is used for Edge enhancement and Histogram Equalization for Image contrast illumination. Hence an improved quality of Image is produced by using Hybrid filters this helps for the efficiency of producing result for any research processing.
Convergence Properties of the BFGS Algoritm

The BFGS method is one of the most famous quasi-Newton algorithms for unconstrained optimization. In 1984, Powell presented an example of a function of two variables that shows that the Polak--Ribiere--Polyak (PRP) conjugate gradient method and the BFGS quasi-Newton method may cycle around eight nonstationary points if each line search picks a local minimum that provides a reduction in the objective function. In this paper, a new technique of choosing parameters is introduced, and an example with only six cyclic points is provided. It is also noted through the examples that the BFGS method with Wolfe line searches need not converge for nonconvex objective functions.
Management of the real-time derived data in a Distributed Real-Time DBMS using the semi-total replication data

In real-time databases, there are data, called sensory. They are regularly updated by periodic update transactions. These data are used to calculate other data, called derived data. At each update of a given sensory data, the derived data which depend on it should be updated. Many studies have been conducted to design architectures for Distributed Real-Time DBMS (DRTDBMS) but excluding real-time derived data. In this paper, we study various policies for updating derived data and apply a mixed method for updating derived data based on a management approach to Quality of Service (QoS) using a semi-total replication as a principle of data distribution.
Flexible Multi-Agent Protocols

In this paper we define a novel technique for the specification of agent protocols in Multi-Agent-Systems. This technique addresses a number of shortcomings of previous Electronic Institution based specifications. In particular, we relax the static specification of agent protocols as state-based diagrams and allow protocols to be defined and disseminated in a flexible manner during agent interaction. Our flexible specification is derived from process algebra and thus forms a sound basis for the verification of such systems.
Higher-Order UnCurrying

AbstractWe present a formal specification of unCurrying for a higher-order, functional language with ML-style let-polymorphism. This specification supports the general unCurrying of functions, even for functions that are passed as arguments or returned as values. The specification also supports partial unCurrying of any consecutive parameters of a function, rather than only unCurrying all of a function's parameters. We present the specification as a deductive system that axiomatizes a judgment relating a source term with an unCurried form of the term. We prove that this system relates only typable terms and that it is correct with respect to an operational semantics. We define a practical algorithm, based on algorithm $${\mathcal{W}}$$ , that implements unCurrying and prove this algorithm sound and complete with respect to the deductive system. This algorithm generates maximally unCurried forms of source terms. These results provide a declarative framework for reasoning about unCurrying and support a richer form of unCurrying than is currently found in compilers for functional languages.
Performance Evaluation of Linear Algebra Routines Performance Evaluation of Linear Algebra Routines

In this paper we presents a tool for the dynamic forecast of performance of linear algebra routine as well as communication between clusters. FAST (Fast Agent ’s System Timer) is a software package allowing client applications to obtain an accurate forecast of routine needs in terms of completion time, memory space, and number of communication, as well as current system availability. FAST relies on existing low-level software packages, i.e. network and host monitoring tools, and some of our developments in sequential and parallel computational routines modeling. The FAST internals and user interface are presented, as well as experimental results and validation on different applications.
Map-Matching Integrity using Multi-Sensor Fusion and Multi- Hypothesis Road Tracking

Efficient and reliable map matching algorithms are essential for Advanced Driver Assistance Systems. While most of the existing solutions fail to provide trustworthy outputs when the situation is ambiguous (road intersections, roundabouts, parallel roads …), we present in this paper a new map-matching method based on a multi-hypothesis road tracking that takes advantage of the geographical database road connectedness to provide a reliable road-matching solution with a confidence indicator that can be used for integrity monitoring purposes. Index Terms - GNSS-based Localization, Map-Matching, Multi-Hypothesis Tracking, Integrity.
Improvement of particle swarm optimization and its application in the earth-rock dam instability risk calculation

In the light of the problem of premature convergence and local convergence in particle swarm optimization (PSO), a clustering coefficient (λ) and a boundary restriction equation are introduced in the model of PSO at first. And a PSO with cyclical migratory behavior (CMPSO) is proposed based on the optimization of particles' work model. And then, the two parameters' characteristics of CMPSO, N which represents migration cycle and K which represents total number of iterations, are tested on benchmark functions. Finally, CMPSO is used to calculate the slope instability risk of Chengbi River Reservoir Earth-Rock Dam. The result shows that CMPSO has a significant increase at speed and precision in calculation compared with PSO, and needs fewer particles. Compared to the result of Monte-carlo simulation, CMPSO also has higher accuracy than PSO in the calculation of slope instability risk.
Recursive estimation of terrestrial magnetic and electric potentials

In this paper we recursively estimate the magnetic and electric potential of the Earth¿s Arctic region. We construct estimates based on data gathered from over 85 magnetometer sources and several radar sites dispersed around the North Pole. The approach to estimating the Arctic polar cap electric potential is through data assimilation based on linear and nonlinear Kalman filters. We demonstrate that the magnetic and electric potential over the Arctic region can be approximately reconstructed from sparse, nonuniform magnetometer and radar data sources.
3× 3 MINORS OF CATALECTICANTS

Secant varieties of Veronese embeddings of projective space are classical varieties whose equations are far from being understood. Minors of catalecticant matrices furnish some of their equations, and in some situations even generate their ideals. Geramita conjectured that this is the case for the secant line variety of the Veronese variety, namely that its ideal is generated by the 3 × 3 minors of any of the “middle” catalecticants. Part of this conjecture is the statement that the ideals of 3 × 3 minors are equal for most catalecticants, and this was known to hold set-theoretically. We prove the equality of 3 × 3 minors and derive Geramita’s conjecture as a consequence of previous work by Kanev.
Body Definition Based on Visuomotor Correlation

This work proposes a plausible approach for a humanoid robot to define its own body based on visuomotor correlation. The high correlation of motion between vision and proprioception informs the robot that a visually moving object is related to the motor function of its own body. When the robot finds a motor-correlated object during motor exploration, visuomotor cues such as body posture and the visual features of the object are stored in visuomotor memory. Then, the robot developmentally defines its own body without prior knowledge on body appearances and kinematics. Body definition is also adaptable for an extended body such as a tool that the robot is grasping. The body movements are generated in the manner of stochastic motor babbling, whereas visuomotor memory biases the babbling to keep the body parts in sight. This ego-attracted bias helps the robot explore the joint space more efficiently. After motor exploration, visuomotor memory allows the robot to anticipate a visual image of its own body from a motor command. The proposed approach was experimentally evaluated with humanoid robot iCub.
Female Masculinity at Work

In this study, the author interviewed 49 self-identified masculine women in the United States to examine how they negotiate stigma in the workplace. Masculine women often negotiate dual stigmas due to both their gender nonconformity and perceived sexual orientation. Participants used a variety of strategies to cope with their stigmatized identity including modifying clothing; incorporating feminine behaviors to counteract masculine appearance; working in high-demand, undesirable jobs; working in male-dominated settings; and opting out of formal work organizations. While some participants experienced mistreatment in male-dominated settings, many reported positive outcomes including strong relationships with male coworkers, opportunities for advancement, and a general comfort in the work environment. Participants challenge Goffman’s notion of sexual orientation as a concealable status, showing that sexual orientation minority women who are gender nonconforming employ strategies similar to members of other visibly stigmatized groups. Findings from this study suggest that researchers addressing sexual orientation minorities should include gender expression as a variable that can influence individual experiences and outcomes. Online slides for instructors who want to use this article for teaching are available on PWQ's website at http://journals.sagepub. com/page/pwq/suppl/index.
Modeling and clustering network-level urban traffic status based on traffic flow assignment ratios

The detected traffic data for single point or link cannot satisfy the needs for network-level traffic status information with the rapid development of the traffic control and guidance systems. This paper proposed a modeling and clustering method for network-level urban traffic status based on the dynamic traffic flow assignment ratios. The traffic assignment ratio matrix model integrates traffic status, topology and relation between links, with the dynamic traffic assignment ratios estimated by Linear Programming. The network-level traffic status is clustered by Self-Organizing Map and the typical patterns are discovered. The experiment proves the efficiency and applicability of this method for network-level traffic status modeling and analyzing.
Multiple moving speaker tracking via degenerate unmixing estimation technique and Cardinality Balanced Multi-target Multi-Bernoulli Filter (DUET-CBMeMBer)

The "cocktail party problem" has always been a challenging problem to solve and many blind source separation algorithms have been proposed as solutions. This problem has mainly been discussed for non-moving sound sources but it still remains for moving sound sources and high acoustic reverberations. The ability to localise and track multiple moving speakers is a pre-requisite to solving this problem. The aim of this paper is to show that a combination of Degenerate Unmixing Estimation Technique and a Cardinality Balanced Multitarget Multi-Bernoulli Filter provides a viable way to track multiple sound sources and subsequently address the problem of sound separation for moving targets.
Attachment as a Moderating Factor Between Social Support, Physical Health, and Psychological Symptoms

This study investigated the extent to which perceived social support functioned as a protective factors, and dimensions of insecure attachment (i.e., avoidant and anxious) functioned as risks factors for physical and psychological health. We explored whether insecure attachment was a mechanism that modified the relationship (i.e., protect against or increases risk) between social support and adult health. Participants were 155 non-traditional adult college students from demographically diverse backgrounds. Students were approached in common areas on campus or in classrooms during break and were asked to complete the questionnaire. Bartholomew and Horowitz’s Attachment Questionnaire assessed avoidant and anxious attachment dimensions, the Brief Social Support Questionnaire assessed perceived social support, and the Memorial Symptom Assessment Scale measured physical and psychological symptoms. Model results indicated that the anxious dimension of insecure attachment was more directly and positively associated with poorer general physical health and psychological symptoms, whereas greater perceived social support was linked with better reported health. However, an interesting pattern emerged with avoidant attachment through a moderated relationship with social support. The absence of a satisfying supportive network was significantly related to poorer physical and psychological health outcomes for those low in avoidant attachment, but not for those high in avoidant attachment. Results from this work suggest that insecure attachment plays a detrimental role in adult health. Perceived social support does not necessarily function as a blanket protective factor for health, as it seemed to offer less benefit to those high in attachment avoidance.
A New Markov Model for Clustering Categorical Sequences

Clustering categorical sequences remains an open and challenging task due to the lack of an inherently meaningful measure of pair wise similarity between sequences. Model initialization is an unsolved problem in model-based clustering algorithms for categorical sequences. In this paper, we propose a simple and effective Markov model to approximate the conditional probability distribution (CPD) model, and use it to design a novel two-tier Markov model to represent a sequence cluster. Furthermore, we design a novel divisive hierarchical algorithm for clustering categorical sequences based on the two-tier Markov model. The experimental results on the data sets from three different domains demonstrate the promising performance of our models and clustering algorithm.