Miracle-dz/UniFAR-FTUs huggingface dataset:
Biochemical Characterization of the DNA Helicase Activity of theEscherichia coli RecQ Helicase*

We demonstrate that RecQ helicase fromEscherichia coli is a catalytic helicase whose activity depends on the concentration of ATP, free magnesium ion, and single-stranded DNA-binding (SSB) protein. Helicase activity is cooperative in ATP concentration, with an apparent S0.5value for ATP of 200 μm and a Hill coefficient of 3.3 ± 0.3. Therefore, RecQ helicase utilizes multiple, interacting ATP-binding sites to mediate double-stranded DNA (dsDNA) unwinding, implicating a multimer of at least three subunits as the active unwinding species. Unwinding activity is independent of dsDNA ends, indicating that RecQ helicase can unwind from both internal regions and ends of dsDNA. The K M for dsDNA is 0.5–0.9 μm base pairs; the k catfor DNA unwinding is 2.3–2.7 base pairs/s/monomer of RecQ helicase; and unexpectedly, helicase activity is optimal at a free magnesium ion concentration of 0.05 mm. Omitting Escherichia coli SSB protein lowers the rate and extent of dsDNA unwinding, suggesting that RecQ helicase associates with the single-stranded DNA (ssDNA) product. In agreement, the ssDNA-dependent ATPase activity is reduced in proportion to the SSB protein concentration; in its absence, ATPase activity saturates at six nucleotides/RecQ helicase monomer and yields a k cat of 24 s− 1. Thus, we conclude that SSB protein stimulates RecQ helicase-mediated unwinding by both trapping the separated ssDNA strands after unwinding and preventing the formation of non-productive enzyme-ssDNA complexes.
Information Measures Based on Sampling Distributions

— Information theory and Statistics play an important role in Biological Sciences when we use information measures for the study of diversity and equitability. In this communication, we develop the link among the three disciplines and prove that sampling distributions can be used to develop new information measures. Our study will be an interdisciplinary and will find its applications in Biological systems.
Robust Polyhedral Regularization

In this paper, we establish robustness to noise perturbations of polyhedral regularization of linear inverse problems. We provide a sufficient condition that ensures that the polyhedral face associated to the true vector is equal to that of the recovered one. This criterion also implies that the $\ell^2$ recovery error is proportional to the noise level for a range of parameter. Our criterion is expressed in terms of the hyperplanes supporting the faces of the unit polyhedral ball of the regularization. This generalizes to an arbitrary polyhedral regularization results that are known to hold for sparse synthesis and analysis $\ell^1$ regularization which are encompassed in this framework. As a byproduct, we obtain recovery guarantees for $\ell^\infty$ and $\ell^1-\ell^\infty$ regularization.
Metaphor, Inference and Domain Independent Mappings

In this paper we provide a formalization of a set of default rules that we claim are required for the transfer of information such as causation, event rate and duration in the interpretation of metaphor. Such rules are domain-independent and are identified as invariant adjuncts to any conceptual metaphor. Furthermore, we show the role that these invariant mappings play in a discourse framework for metaphor interpretation.
Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity

Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein–ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art “fixed backbone” design methods perform poorly on these tests, we develop a new “coupled moves” design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein – ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.
Continuing bonds with the living: bereaved parents’ narratives of their emotional relationship with their children

Abstract The death of a child can be seen as one of the most devastating experiences for parents which can result in a unique and enduring grief. Parents with surviving children face the task of navigating their own grief while continuing to parent. This narrative inquiry explores bereaved parents’ stories of their emotional relationship with their surviving children. Parents told stories of emotional connection and disconnection with surviving children, influenced by the competing and potentially incompatible tasks of ‘parenting’ and ‘grieving’. The need for a relational focus to bereavement research and practice is highlighted. The findings demonstrate the need for clinicians to provide i) parents an opportunity to explore their sometimes contradicting and troubling experiences of grief and parenting and ii) children with support to make sense of their experiences in relation to the parent-child relationship.
Efficient extraction of ontologies from domain specific text corpora

Extracting ontological relationships (e.g., ISA and HASA) from free-text repositories (e.g., engineering documents and instruction manuals) can improve users' queries, as well as benefit applications built for these domains. Current methods to extract ontologies from text usually miss many meaningful relationships because they either concentrate on single-word terms and short phrases or neglect syntactic relationships between concepts in sentences. We propose a novel pattern-based algorithm to find ontological relationships between complex concepts by exploiting parsing information to extract multi-word concepts and nested concepts. Our procedure is iterative: we tailor the constrained sequential pattern mining framework to discover new patterns. Our experiments on three real data sets show that our algorithm consistently and significantly outperforms previous representative ontology extraction algorithms.
Validation of the schema mode concept in personality disordered offenders

Purpose A core element of Schema Therapy (ST) is ‘schema modes’ or fluctuating emotional states. ST assumes that particular personality pathology consists of specific combinations of maladaptive schema modes. There is confirmatory evidence for the modes hypothesized to be central to borderline and narcissistic personality disorder (PD) in non-forensic patients. In this study, we tested three aspects of the construct validity of schema modes in cluster-B personality disordered offenders, examining its factorial validity, and the relations among personality disorders and violence risk. Method Our sample consisted of 70 offenders who were diagnosed with an antisocial, borderline, or narcissistic PD. Schema modes were assessed with the Schema Mode Inventory (SMI), personality disorders with the Schedule for Nonadaptive and Adaptive Personality-Forensic Version (SNAP-FV), and violence risk with the Historical, Clinical, and Risk management scheme (HCR-20V2). Results When controlling for the two other PDs, three schema mode factors distinguished antisocial PD as a disorder involving both low scores on internalizing and high scores on externalizing modes, and borderline PD as involving high scores on internalizing modes. Furthermore, the externalizing schema modes were a significant predictor for violence risk inside the hospital. Conclusions The hypothesized mode models were partially supported for all three PDs. The findings thus provide some support for the construct validity of schema modes in a forensic sample.
Effect of Line-Width Variation in Radio over Fiber System Based On Optical Single Side Band for Short Haul Communication

Carrier to Noise Ratio (CNR) has been investigated for radio over fiber systems including the effects of variation in the RF oscillator linewidth in this paper. Optical Single sideband si gnal is studied as it has tolerance for power degradation due to dispersi on effects over a length of fiber. Investigations have been made out for Radio frequency of 30 GHz, with a continuous wave (CW) laser source of 1550 nm. CNR has been evaluated using Power Spectral Density(PSD) function.CNR is studied varying RF oscillator linewidth and RF oscillator linewidth for 2 Km fibe r with chromatic dispersion D=17 ps/Km nm. Kewwords: RoF, CNR, MZM, OSSB, Power degradation.
Comparative evaluation of peer-to-peer systems using PeerfactSim.KOM

Comparative evaluations of peer-to-peer protocols through simulations are a viable approach to judge the performance and costs of the individual protocols in large-scale networks. In order to support this work, we enhanced the peer-to-peer systems simulator PeerfactSim.KOM with a fine-grained analyzer concept, with exhaustive automated measurements and gnuplot generators as well as a coordination control to evaluate a set of experiment setups in parallel. Thus, by configuring all experiments and protocols only once and starting the simulator, all desired measurements are performed, analyzed, evaluated and combined, resulting in a holistic environment for the comparative evaluation of peer-to-peer systems.
What Role Does Private Equity Play When Leveraged Buyouts Go Public

This research studies buyout sponsors’ incentive and corporate control in Reverse Leveraged Buyouts (RLBOs). By and large, buyout sponsors take LBOs public when LBO structure has achieved the most improvement. Contrary to previous literature, RLBO firms do not experience significant operating performance deterioration after going public. In this study, I empirically measure sponsor incentive using LBO relative size to buyout sponsor capital as a proxy. Buyout sponsors with weaker incentives are more likely to quick flip a deal; quick flip leads to poorer subsequent performance. Generally, buyout sponsors’ decisions to take LBOs public are consistent with a partial equilibrium. I find a negative relationship between the buyout sponsors’ ownership before IPO and the firms’ long-term value after IPO. Buyout sponsors maximize benefits of control through staged exit strategy. For example, they are more likely to continue to hold equity in cash-rich firms while sell their stakes through subsequent takeovers in firms with higher ownership concentration. Overall, this paper helps us to understand buyout sponsors’ organizational role in RLBOs.
An 81.6 GOPS Object Recognition Processor Based on NoC and Visual Image Processing Memory

An 81.6 GOPS object recognition processor is developed by using NoC and visual image processing (VIP) memory. SIFT (scale invariant feature transform) object recognition requires huge computing power and data transactions among tasks. The chip integrates 10 SIMD PEs for data/task level parallelism while the NoC facilitates inter-PE communications. The VIP memory searches local maximum pixel inside a 3times3 window in a single cycle providing 65.6 GOPS. The proposed processor achieves 15.9 fps SIFT feature extraction at 200 MHz.
The Significance of Multimodality/Multiliteracies in Iranian EFL Learners’ Meaning- Making Process

The main objective of this study was to investigate how Iranian EFL learners used their literacy practices and multimodal resources to mediate interpretation and representation of an advertisement text and construct their understanding of it. Fifteen female adolescents at an intermediate level of proficiency read the «مبلمان برليان» (“Brelian Furniture”) advertisement text and re-created their understandings in pictures and sentences. The data was analyzed based on Kress and Van Leeuwen’s (1996, 2001) theory of social semiotics. The findings suggest that students situated the meanings of the advertisement texts in specific contexts that reflected their own social and cultural experiences. Furthermore, the students demonstrated that the use of multimodal resources had the potential to enhance language and literacy learning in a way that was transformative and was affected by their identities. In addition, the use of multimodal/multiliteracies pedagogy permitted the students to enter into text composition from different paths. Finally, multimodal/multiliteracies pedagogy could foster critical literacy practices by offering EFL students the opportunities to create new identities and challenge discursive practices that marginalize them. The implications of the findings are also discussed.
Generalized Gaussian mixture model

The parameters estimation of mixture distributions is an important task in statistical signal processing, Pattern recognition, blind equalization and other modern statistical tasks often call for mixture estimation. This paper aims to provide a realistic distribution based on Mixture of Generalized Gaussian distribution (MGG), which has the advantage to characterize the variability of shape parameter in each component in the mixture. We propose a formulation of the Expectation Maximization (EM) algorithm under Generalized Gaussian distribution. For this, two different methods are proposed to include the shape parameter estimation. In the first method a derivation of the Likelihood function is used to update the mixture parameters. In the second approach we propose an extension of the “classical” (EM) algorithm and to estimate the shape parameter in terms of Kurtosis. The Kullback-Leibler divergence (KLD) is used to compare, and evaluate these algorithms of MGG parameters estimation. An application of this technique is considered for modeling load distribution which exhibits an heterogeneity with a high variability of shape parameters 1.
Fixed-Parameter Algorithms in Phylogenetics

This chapter surveys the use of fixed-parameter algorithms in phylogenetics. A central computational problem in this field is the construction of a likely phylogeny (genealogical tree) for a set of species based on observed differences in the phenotype, differences in the genotype, or given partial phylogenies. Ideally, one would like to construct so-called perfect phylogenies, which arise from an elementary evolutionary model, but in practice one must often be content with phylogenies whose "distance from perfection" is as small as possible. The computation of phylogenies also has applications in seemingly unrelated areas such as genomic sequencing and finding and understanding genes. The numerous computational problems arising in phylogenetics are often NP-complete, but for many natural parametrizations they can be solved using fixed-parameter algorithms.
Electronic Textiles: Wearable Computers, Reactive Fashion, and Soft Computation

Abstract Electronic textiles, also referred to as smart fabrics, are quite fashionable right now. Their close relationship with the field of computer wearables gives us many diverging research directions and possible definitions. On one end of the spectrum, there are pragmatic applications such as military research into interactive camouflage or textiles that can heal wounded soldiers. On the other end of the spectrum, work is being done by artists and designers in the area of reactive clothes: “second skins” that can adapt to the environment and to the individual. Fashion, health, and telecommunication industries are also pursuing the vision of clothing that can express aspects of people's personalities, needs, and desires or augment social dynamics through the use and display of aggregate social information. In my current production-based research, I develop enabling technology for electronic textiles based upon my theoretical evaluation of the historical and cultural modalities of textiles as they relate to future computational forms. My work involves the use of conductive yarns and fibers for power delivery, communication, and networking, as well as new materials for display that use electronic ink, nitinol, and thermochromic pigments. The textiles are created using traditional textile manufacturing techniques: spinning conductive yarns, weaving, knitting, embroidering, sewing, and printing with inks.
POSTER: Toward Automating the Generation of Malware Analysis Reports Using the Sandbox Logs

In recent years, the number of new examples of malware has continued to increase. To create effective countermeasures, security specialists often must manually inspect vast sandbox logs produced by the dynamic analysis method. Conversely, antivirus vendors usually publish malware analysis reports on their website. Because malware analysis reports and sandbox logs do not have direct connections, when analyzing sandbox logs, security specialists can not benefit from the information described in such expert reports. To address this issue, we developed a system called ReGenerator that automates the generation of reports related to sandbox logs by making use of existing reports published by antivirus vendors. Our system combines several techniques, including the Jaccard similarity, Natural Language Processing (NLP), and Generation (NLG), to produce concise human-readable reports describing malicious behavior for security specialists.
Bio-chemical sensor using polyaniline nanofibers for sensing amino-group type of gas

Traditionally, polyaniline was used for sensing ammonia (NH3 ) gas due to the change of conductivity. By integrated with surface acoustic wave sensor (SAW) for sensing the amino-group type of gas, a novel bio-chemical sensor had been developed. The mechanism of the SAW sensor is that the change of gravity results in the change of physical characteristics of SAW sensor. In order to increase the absorbability of the polymer, we use the nano structure to increase the surface area ratio that can make gaseous molecular being absorbed onto the nano structure quickly. Three kinds of solvent vapor were tested: ammonium hydroxide, triethylamine, and acetone
Efficient Channel-Hopping Rendezvous Algorithm Based on Available Channel Set

In cognitive radio networks, rendezvous is a fundamental operation by which two cognitive users establish a communication link on a commonly-available channel for communications. Some existing rendezvous algorithms can guarantee that rendezvous can be completed within finite time and they generate channel-hopping (CH) sequences based on the whole channel set. However, some channels may not be available (e.g., they are being used by the licensed users) and these existing algorithms would randomly replace the unavailable channels in the CH sequence. This random replacement is not effective, especially when the number of unavailable channels is large. In this paper, we design a new rendezvous algorithm that attempts rendezvous on the available channels only for faster rendezvous. This new algorithm, called Interleaved Sequences based on Available Channel set (ISAC), constructs an odd sub-sequence and an even sub-sequence and interleaves these two sub-sequences to compose a CH sequence. We prove that ISAC provides guaranteed rendezvous (i.e., rendezvous can be achieved within finite time). We derive the upper bound on the maximum time-to-rendezvous (MTTR) to be O(m) (m is not greater than Q) under the symmetric model and O(mn) (n is not greater than Q) under the asymmetric model, where m and n are the number of available channels of two users and Q is the total number of channels (i.e., all potentially available channels). We conduct extensive computer simulation to demonstrate that ISAC gives significantly smaller MTTR than the existing algorithms.
Associations between subunit ectodomains promote T cell antigen receptor assembly and protect against degradation in the ER

The T cell antigen receptor (TCR) is an oligomeric protein complex made from at least six different integral membrane proteins (alpha beta gamma delta epsilon and zeta). The TCR is assembled in the ER of T cells, and correct assembly is required for transport to the cell surface. Single subunits and partial receptor complexes are retained in the ER where TCR alpha, beta, and CD3 delta chains are degraded selectively. The information required for the ER degradation of the TCR beta chain is confined to the membrane anchor of the protein (Wileman et al., 1990c; Bonifacino et al., 1990b). In this study we show that the rapid degradation of the TCR beta chain is inhibited when it assembles with single CD3 gamma, delta, or epsilon subunits in the ER, and have started to define the role played by transmembrane anchors, and receptor ectodomains, in the masking proteolytic targeting information. Acidic residues within the membrane spanning domains of CD3 subunits were essential for binding to the TCR beta chain. TCR beta chains and CD3 subunits therefore interact via transmembrane domains. However, when sites of binding were restricted to the membrane anchor of the TCR beta chain, stabilization by CD3 subunits was markedly reduced. Interactions between membrane spanning domains were not, therefore, sufficient for the protection of the beta chain from ER proteolysis. The presence of the C beta domain, containing the first 150 amino acids of the TCR ectodomain, greatly increased the stability of complexes formed in the ER. For assembly with CD3 epsilon, stability was further enhanced by the V beta amino acids. The results showed that the efficient neutralization of transmembrane proteolytic targeting information required associations between membrane spanning domains and the presence of receptor ectodomains. Interactions between receptor ectodomains may slow the dissociation of CD3 subunits from the beta chain and prolong the masking of transmembrane targeting information. In addition, the close proximity of TCR and CD3 ectodomains within the ER may provide steric protection from the action of proteases within the ER lumen.
Robust Boundary Detection With Adaptive Grouping

This paper presents a perceptual grouping algorithm that performs boundary extraction on natural images. Our grouping method maintains and updates a model of the appearance of the image regions on either side of a growing contour. This model is used to change grouping behaviour at run-time, so that, in addition to following the traditional Gestalt grouping principles of proximity and good continuation, the grouping procedure favours the path that best separates two visually distinct parts of the image. The resulting algorithm is computationally efficient and robust to clutter and texture. We present experimental results on natural images from the Berkeley Segmentation Database and compare our results to those obtained with three alternate grouping methods.