Miracle-dz/UniFAR-FTUs huggingface dataset:
PhyloSource : An Interactive Phylogenetic Relationship Repository

Use of phylogenetic relationship computation tools such as ClustalW (Thompson et al., 1994) can be very effective in computationally analyzing gene functions. ClustalW produces the phylogenetic distances between the target gene and its homologs. The outcome of the program can be presented in a tree-like style. This graphical display allows scientists to visualize evolutionary relationship between similar genes from multiple species. Knowing such evolutionary relationships can be very useful in understanding functional variations between homologous genes, identifying subfamily-specific sequence features, and conducting advanced study of evolution such as mosaic genomes (e.g., Koonin et al., 1997; Olendzenski et al., 1998) and horizontal gene transfer (e.g., Doolittle, 1999; Olendzenski et al., 2000). One problem in utilizing the evolutionary relationships in the gene function study is the sheer amount of computational work that a scientist needs to undertake. One would have to gather completed species sequence data from the primary sequence data source(s) such as GenBank. She then would have to run programs like BLAST and ClustalW in tandem repeatedly. Conducting such computationally extensive processes may take days or weeks depending on the computational power the scientist is equipped with. In addition, maintaining intermediate and final analysis data would require use of scalable repository system such a database management system. Another problem is the data dependency and extension. Whenever new sequence data is deposited to the primary sequence source, new computation should be done to derive the most upto-date phylogenetic relationships. Yet another problem is that once phylogenetic relationships are derived, there should be a systematic way of associating this data set with other related data. Considering all these computational issues, taking advantage of phylogenetic relationships for gene functional studies is not something that an ordinary biology laboratory would easily be able to undertake. We believe that it is desirable for one group with sufficient computing resources to develop a comprehensive repository containing phylogenetic relationships and become responsible for maintaining and sharing it with the rest of the genome analysis community. We made an effort to develop such a repository and it resulted in, what we call, PhyloSource. Currently it contains phylogenetic relationships of 21 species whose sequencing data has been reported complete or near complete. The goal of this work is to present the computation issues that we have dealt with in developing this repository, the methodology that we were able to successfully adopt, and the challenges that we are currently facing.
Lungprints: An alternative view in multiple-stream time-series analysis of bioimpedance signals

In this paper we introduce Lungprints, which are 2D barcode-pattern like images representing ventilation characteristics of a patient. Recent advances in impedance imaging, namely electrical impedance tomography (EIT), allow for the development of an inexpensive, non-ionizing and non-invasive way of monitoring lung ventilation. Various methods have been proposed for the characterization of temporal lung tissue behaviour during ventilation using EIT. Impedance images are built in real time (13 frames/sec) by processing the measured voltage-streams on the thoracic surface. However, impedance recovery is a highly non-linear ill-posed inverse problem, thus the generated images are highly fuzzy and blurry. The latter characteristics impede robust and precise feature extraction and quantification, which could be used as suitable features for lung signal analysis and diagnosis. In this light, we propose an automatic pipeline for lung bioimpedance signal representation and analysis using rapid lungprint classification. We train a single-class vector machine (SVM) classifier, which estimates the parameters of the class from a dictionary of features, composed of moments extracted from a multi-scale representation of healthy patient lungprints onto a translation invariant set of atoms, namely stationary wavelets. Results show the appropriateness of the proposed method in automatic lung signal representation and classification and its potential advantages not only as a bed-side lung monitoring tool, but in other areas such as multiple stream time-series analysis where data streams exhibit cyclic behavior.
Instructional Design and the Curriculum Development Process.

For curriculum designed for numerous presentations by a variety of instructors, a systems approach offers schools a cost-effective, integrated process already used by the military, corporations, and third-world nations. A process for improving student achievement through the systematic design, development, and evaluation of instruction is currently available but not widely used by the public schools. The process is referred to as the systems approach, and those who use it are usually referred to as instructional designers. The Instructional Design Process The "systems approach" label indicates that a set of interrelated procedures is used to achieve a predetermined outcome. The process includes a feedback loop that indicates the extent to which the instruction has been effective and how it might be revised. There is no single systems approach. Andrews and Goodson (1980) have indicated that at least 40 different models have been documented in the literature However, the models have a striking degree of similarity. Figure 1 is based primarily on the common elements identified by Andrews and Goodson. Historical Perspective The general systems approach first became well known to the public when it was applied to the development of large weapons systems by military contractors in the 1950s. However , the term was not used in education until 10 to 20 years later. The '60s saw the emergence of the components that eventually would be combined to become the instructional design systems approach. Interestingly enough, a number of these components were the direct result of work done on various curriculum development projects. Robert Glaser and researchers at the University of Pittsburgh were among the first to develop individualized instructional packages for elementary children. As they developed instructional objectives, Glaser became aware of the necessity of including test items that directly measured the behaviors described in the objectives. This process of matching test items to objectives became known as criterion-refer-enced testing and is a key component of the systems approach. Robert Gagne was a consultant to the Maryland Mathematics Project when he developed his procedures for identifying learning hierarchies. Rather than accepting a list of skills that might have been identified by a subject matter specialist, for each stated instructional goal Gagne asked the question, 'What does the student have to know or be able to do in order to learn to perform the instructional goal? " The answer was the identification of several subordinate skills that, when combined with additional instruction …
AutoBot: a versatile platform for management of legacy applications in the cloud

Legacy distributed applications are moving to the cloud in order to reduce operational costs and provide more scalable services to users. These applications are built by interconnecting independently developed packages and services distributed over multiple machines. The installation, deployment and management of such applications on the cloud is hard, and usually performed either manually or by writing customized scripts. This is highly error-prone and it has been shown that misconfiguration is the root of many errors. We present AutoBot, a system for configuring, installing, and managing complex legacy application stacks deployed on the cloud which dynamically evolve in time. AutoBot consists of three components: a novel and simple model describing components' configuration properties and inter-dependencies; a dynamic deployment and configuration protocol ensuring the correct resolution of these inter-dependencies; a runtime system that guarantees the correct deployment of the application across multiple machines as well as the management of the deployed system. This reduces the tedious and error-prone manual process of application configuration, installation, and management. We have implemented and used AutoBot to successfully host a number of applications. In this paper, we specifically describe our experiences in using AutoBot to manage a traditional N-tier Java application in the cloud. In order to check that this protocol works as expected, we also formally specify and verify some interesting properties.
Digital Commons @ Michigan Tech Digital Commons @ Michigan Tech

Background: Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. Results: A bottom-up graphic Gaussian model (GGM) algorithm was developed for constructing ML-hGRN operating above a biological pathway using small-to medium-sized microarray or RNA-seq data sets. The algorithm first placed genes of a pathway at the bottom layer and began to construct a ML-hGRN by evaluating all combined triple genes: two pathway genes and one regulatory gene. The algorithm retained all triple genes where a regulatory gene significantly interfered two paired pathway genes. The regulatory genes with highest interference frequency were kept as the second layer and the number kept is based on an optimization function. Thereafter, the algorithm was used recursively to build a ML-hGRN in layer-by-layer fashion until the defined number of layers was obtained or terminated automatically. Conclusions: We validated the algorithm and demonstrated its high efficiency in constructing ML-hGRNs governing biological pathways. The algorithm is instrumental for biologists to learn the hierarchical regulators associated with a given biological pathway from even small-sized microarray or RNA-seq data sets.
The Symbiotic Neutron Star Binary GX 1+4/V2116 Ophiuchi

We present extensive optical, infrared, and X-ray observations of the S-type symbiotic low-mass X-ray binary GX 1+4/V2116 Oph, which consists of a 2 minute X-ray pulsar accreting from an M6 III giant. This is the only symbiotic system definitely known to contain a neutron star. The mean observed spectral type of the X-ray-heated mass donor is M5 III. The steady interstellar extinction toward the binary (AV = 5.0 ± 0.6) contrasts the variable hydrogen column density inferred from X-ray measurements, most likely evidence for a variable stellar wind. The mass donor is probably near the tip of the first-ascent red giant branch, in which case the system is 3-6 kpc distant and has an X-ray luminosity of ~1037 ergs s-1. It is also possible, though less likely, that the donor star is just beginning its ascent of the asymptotic giant branch, in which case the system is 12-15 kpc distant and has an X-ray luminosity of ~1038 ergs s-1. However, our measured AV argues against such a large distance. We show that the dense (Ne ~ 109 cm-3) emission-line nebula enshrouding the binary is powered by ultraviolet radiation from an accretion disk. The emission-line spectrum constrains the temperature profile and inner radius of the disk (and thus the pulsar's magnetic field strength), and we mention the implications this has for explaining the accretion torque reversals observed in the pulsar. We also show that the binary period must be ≳100 days and is most likely ≳260 days, which makes GX 1+4 the only known low-mass X-ray binary with Porb > 10 days. If the mass donor fills its Roche lobe, the mass transfer rate must be highly super-Eddington, which requires considerable mass loss from the binary. We discuss the alternative possibility that the accretion disk forms from the slow, dense stellar wind expected from the red giant.
SURVEY ON SCORE NORMALIZATION : A CASE OF RESULT MERGING IN DISTRIBUTED INFORMATION RETRIEVAL

Merging the outputs of different search engines or information sources in response to a query has been shown to improve performance. In most cases, scores produced by different information sources are not comparable: merging techniques are often segregated into a score normalization step followed by a combination step. The Combination step is usually straight forward and has been an area of active research. However, the normalization step has received less attention; in particular a peculiar attribute such as diversification is largely missing in most Result Merging studies. This survey seeks to explore the various domains of score normalization, especially the results merging phase of a Distributed Information Retrieval environment, and propose a general framework to diversify score normalization through the use of the covariance principle. Key-Words: Machine learning , Classification approach , Distributed Information retrieval , Result merging , Information Retrieval
Low Power and Enhanced Noise Margins SRAM Using Novel Asymmetric FinFETs

This paper proposes a asymmetric FinFET (Fin shaped Field Effect Transistor) for robust and low power SRAM (Static Random Access Memory). This FinFET device uses Asymmetric Drain (AD), Asymmetric Drain Spacer Extension (ADSE) and Asymmetric Lateral Diffusion (ALD) techniques. The proposed structure exploits asymmetrical behavior of current to improve read-write stability for SRAM without compromising the cell area. As the asymmetry in Ids (drain to source) and Isd (source to drain) increases, improvement is observed in read, write and static noise margins. The write noise margin (WNM) and read noise margin (RNM) behavior is contradictory to each other, increase in one leads to decrease in other. It has been observed that by using asymmetric FinFETs altogether an overall improvement in static, read and write noise margins are 23.5, 19.3 and 12.4, percent respectively. Reduction in Average power is observed 21 percent.
Towards developing assistive haptic feedback for visually impaired internet users

Haptic technologies are thought to have the potential to help blind individuals overcome the challenges experienced when accessing the Web. This paper proposes a structured participatory-based approach for developing targeted haptic sensations for purposes of web page exploration, and reports preliminary results showing how HTML elements can be represented through the use of force-feedback. Findings are then compared with mappings from previous studies, demonstrating the need for providing tailored haptic sensations for blind Internet users. This research aims to culminate in a framework, encompassing a vocabulary of haptic sensations with accompanying recommendations for designers to reference when developing inclusive web solutions.
Four types of e ¤ ect modi cation-a classi cation based on directed acyclic graphs

By expressing the conditional causal risk di¤erence as a sum of products of stratum speci c risk di¤erences and conditional probabilities, it is possible to give a classi cation of the types of causal relationships that can give rise to e¤ect modi cation on the risk di¤erence scale. Directed acyclic graphs make clear the necessary causal relationships for a particular variable to serve as an e¤ect modi er for the causal risk di¤erence concerning two other variables. The directed acyclic graph causal framework thereby gives rise to a four-fold classi cation for e¤ect modi cation: direct e¤ect modi cation, indirect e¤ect modi cation, e¤ect modi cation by proxy and e¤ect modi cation by a common cause. Brief discussion is given to the case of multiple e¤ect modi cation relationships and multiple e¤ect modi ers as well as measures of e¤ect other than that of the causal risk di¤erence. Key Words: Causal inference; directed acyclic graphs; e¤ect modi cation; interaction. Directed acyclic graphs have been used as causal diagrams in epidemiologic research for a variety of purposes. Directed acyclic graphs have been used to represent causal relations amongst variables; 3 they have been used extensively to determine the variables for which it is necessary to control for confounding in order to estimate causal e¤ects; 2;4 5 more recently they have been used by Hernán et al. to provide a classi cation of the types of causal relationships that can give rise to selection bias. In this paper we follow their work by using directed acyclic graphs to provide a classi cation of the types of causal relationships that can give rise to e¤ect modi cation. Speci cally, we consider what relationships an e¤ect modi er variable may exhibit in relation to the variable constituting the cause and the variable constituting the e¤ect. Doing so yields a structural classi cation of e¤ect modi cation; the classi cation is structural in that it makes reference to the structure of the causal directed acyclic graph. We rst provide some discussion of the various measures of e¤ect used to assess e¤ect modi cation. We will then focus on the causal risk di¤erence as a measure of e¤ect by which e¤ect modi cation is assessed (though much of the discussion applies also to other measures of e¤ect as well) and we use directed acyclic graphs to provide a classi cation of di¤erent types of e¤ect modi cation. Extensions to conditioning on multiple items and to scales other than the risk di¤erence are discussed at the papers conclusion and in Appendix 1.
Achieving Global Shapes Through Local Goals in Reconfigurable Robotics

This project looks at the problem of creating an online distributed control method to solve the reconfiguration problem in reconfigurable robotics. We look at breaking down the global reconfiguration task into local tasks that can be performed robustly by the individual modules in order to achieve the global reconfiguration task. This is done by the modules first learning local reconfiguration skills offline. The modules then apply these skills individually online to achieve local goals in order to achieve the global goal as a system. Ideas are taken from transfer learning, work on local contexts [19], and work on sequential decision making [12]. The method devised promises to be useful in addressing the reconfiguration problem for reconfigurable robots but problems with the task assignment hindered its performance and hence requires further investigation.
Beam Polarization at the ILC: the Physics Impact and the Accelerator Solutions

In this contribution accelerator solutions for polarized beams and their impact on physics measurements are discussed. Focus are physics requirements for precision po-larimetry near the interaction point and their realization with polarized sources. Based on the ILC baseline programme as described in the Reference Design Report (RDR), recent developments are discussed and evaluated taking into account physics runs at beam energies between 100 GeV and 250 GeV, as well as calibration runs on the Z-pole and options as the 1TeV upgrade and GigaZ.
EQVMP: Energy-efficient and QoS-aware virtual machine placement for software defined datacenter networks

To provide effective and reliable services, cloud datacenters need parallel computing and virtualization techniques. This work presents an improved virtual machine (VM) placement mechanism, called Energy efficiency and Quality of Service (QoS) aware VM Placement (EQVMP) to overcome the problem of unbalanced traffic load in switching on and off VMs for the purpose of energy saving. EQVMP combines three key techniques: (1) hop reduction, (2) energy saving and (3) load balancing. Hop reduction can regroup VMs to lower the traffic load among them. Energy saving techniques aim at choosing the appropriate servers. The proposed load balancing updates VM placement periodically. Our experimental results show that the proposed scheme can lower energy consumption and maintain QoS. We propose an evaluation score [1] to assess VM placement in terms of energy, delay and throughput. Comparing to other existing placement policies, our proposed mechanism can enhance system throughput by 25% and can have better evaluation score.
Classification of Motor Imagery EEG Signals Based on Energy Entropy

Feature extraction and classification of EEG signals is core issues on EEG-based brain computer interface (BCI). Typically, such classification has been performed using signals from a set of selected EEG sensors. Because EEG sensor signals are mixtures of effective signals and noise, which has low signal-to-noise ratio, motor imagery EEG signals can be difficult to classification. Energy entropy was used to preprocess motor imagery EEG data, and the Fisher class separability criterion was used to extract features. Finally, classification of four types motor imagery EEG was performed by a method based on the statistical theory. An average of 85% classification accuracy of the six type combination and the three subjects was achieved. The results showed that motor imagery EEG signals can be extracted using energy entropy and that these extracted features offered clear advantages for classification.
The evolution of barium and europium in local dwarf spheroidal galaxies

By means of a detailed chemical evolution model, we follow the evolution of barium and europium in four Local Group Dwarf Spheroidal Galaxies, in order to set constraints on the nucleosynthesis of these elements and on the evolution of this type of galaxies compared with the Milky Way. The model, which is able to reproduce several observed abundance ratios and the present day total mass and gas mass content of these galaxies, adopts up to date nucleosynthesis and takes into account the role played by supernovae of different types (II, Ia) allowing us to follow in detail the evolution of several chemical elements (H, D, He, C, N, O, Mg, Si, S, Ca, Fe, Ba and Eu). By assuming that barium is a neutron capture element produced in low mass AGB stars by s-process but also in massive stars (in the mass range 10 - 30 M⊙) by r-process, during the explosive event of supernovae of type II, and that europium is a pure r-process element synthesized in massive stars also in the range of masses 10 - 30 M⊙, we are able to reproduce the observed [Ba/Fe] and [Eu/Fe] as functions of [Fe/H] in all four galaxies studied. We confirm also the important role played by the very low star formation efficiencies ( = 0.005 - 0.5 Gyr −1 ) and by the intense galactic winds (6-13 times the star formation rate) in the evolution of these galaxies. These low star formation efficiencies (compared to the one for the Milky Way disc) adopted for the Dwarf Spheroidal Galaxies are the main reason for the differences between the trends of [Ba/Fe] and [Eu/Fe] predicted and observed in these galaxies and in the metal-poor stars of our Galaxy. Finally, we provide predictions for Sagittarius galaxy for which data of only two stars are available.
TATO: Leveraging on Multiple Strategies for Semantic Textual Similarity

In this paper, we describe the TATO system which participated in the SemEval-2015 Task 2a: “Semantic Textual Similarity (STS) for English”. Our system is trained on published datasets from the previous competitions. Based on some machine learning techniques, it combines multiple similarity measures of varying complexity ranging from simple lexical and syntactic similarity measures to complex semantic similarity ones to compute semantic textual similarity. Our final model consists of a simple linear combination of about 30 main features out of a numerous number of features experimented. The results are promising, with Pearson’s coefficients on each individual dataset ranging from 0.6796 to 0.8167 and an overall weighted mean score of 0.7422, well above the task baseline system.