Miracle-dz/UniFAR-FTUs huggingface dataset:
Progress in protein–protein docking: Atomic resolution predictions in the CAPRI experiment using RosettaDock with an improved treatment of side‐chain flexibility

RosettaDock uses real‐space Monte Carlo minimization (MCM) on both rigid‐body and side‐chain degrees of freedom to identify the lowest free energy docked arrangement of 2 protein structures. An improved version of the method that uses gradient‐based minimization for off‐rotamer side‐chain optimization and includes information from unbound structures was used to create predictions for Rounds 4 and 5 of CAPRI. First, large numbers of independent MCM trajectories were carried out and the lowest free energy docked configurations identified. Second, new trajectories were started from these lowest energy structures to thoroughly sample the surrounding conformation space, and the lowest energy configurations were submitted as predictions. For all cases in which there were no significant backbone conformational changes, a small number of very low‐energy configurations were identified in the first, global search and subsequently found to be close to the center of the basin of attraction in the free energy landscape in the second, local search. Following the release of the experimental coordinates, it was found that the centers of these free energy minima were remarkably close to the native structures in not only the rigid‐body orientation but also the detailed conformations of the side‐chains. Out of 8 targets, the lowest energy models had interface root‐mean‐square deviations (RMSDs) less than 1.1 Å from the correct structures for 6 targets, and interface RMSDs less than 0.4 Å for 3 targets. The predictions were top submissions to CAPRI for Targets 11, 12, 14, 15, and 19. The close correspondence of the lowest free energy structures found in our searches to the experimental structures suggests that our free energy function is a reasonable representation of the physical chemistry, and that the real space search with full side‐chain flexibility to some extent solves the protein–protein docking problem in the absence of significant backbone conformational changes. On the other hand, the approach fails when there are significant backbone conformational changes as the steric complementarity of the 2 proteins cannot be modeled without incorporating backbone flexibility, and this is the major goal of our current work. Proteins 2005;60:187–194. © 2005 Wiley‐Liss, Inc.
Inference Instruction to Support Reading Comprehension for Elementary Students With Learning Disabilities

Making inferences during reading is a critical standards-based skill and is important for reading comprehension. This article supports the improvement of reading comprehension for students with learning disabilities (LD) in upper elementary grades by reviewing what is currently known about inference instruction for students with LD and providing detailed suggestions and a five-step process for teaching students to make text-connecting and knowledge-based inferences while reading. By bolstering this key reading comprehension skill in the upper elementary grades, teachers can better prepare students for the increased reading comprehension demands of middle school.
Fluctuations of Fitness Distributions and the Rate of Muller’s Ratchet

The accumulation of deleterious mutations is driven by rare fluctuations that lead to the loss of all mutation free individuals, a process known as Muller’s ratchet. Even though Muller’s ratchet is a paradigmatic process in population genetics, a quantitative understanding of its rate is still lacking. The difficulty lies in the nontrivial nature of fluctuations in the fitness distribution, which control the rate of extinction of the fittest genotype. We address this problem using the simple but classic model of mutation selection balance with deleterious mutations all having the same effect on fitness. We show analytically how fluctuations among the fittest individuals propagate to individuals of lower fitness and have dramatically amplified effects on the bulk of the population at a later time. If a reduction in the size of the fittest class reduces the mean fitness only after a delay, selection opposing this reduction is also delayed. This delayed restoring force speeds up Muller’s ratchet. We show how the delayed response can be accounted for using a path-integral formulation of the stochastic dynamics and provide an expression for the rate of the ratchet that is accurate across a broad range of parameters.
Optimal Tracking and Identification of Paths for Industrial Robots

This paper presents results from time-optimal path tracking for industrial robots. More specifically, three subproblems are studied and experimentally evaluated. The first is a contact-force control approach for determining the geometric robot motion, such that the tool centre point of the robot is moved according to the specification. The second problem is off-line solution of the optimisation problem describing the time-optimal path tracking problem, by using software which allows highlevel implementation and solution of optimisation problems. The third problem is robust control of the robot during real-time path tracking based on the optimisation results determined off-line. An earlier developed control structure for robust control is implemented and tested in a robot system. This paper discusses the theory behind time-optimal path tracking and presents experimental results. Both contact-force controlled path identification and real-time path tracking of the identified path are evaluated on a 6-DOF industrial robot of type IRB140 from ABB. (Less)
Rapid Memory Reactivation Report Revealed by Oscillatory Entrainment

Episodic memory refers to humans’ unique ability to mentally reconstruct past events. Neurocomputational models predict that remembering entails the reinstatement of brain activity that was present when an event was initially experienced [1–5], a claim that has recently gained support from functional imaging work in humans [6–14]. The nature of this reactivation, however, is still unclear. Cognitive models claim that retrieval is set off by an early reactivation of stored memory representations (‘‘ecphory’’) [15–17]. However, reinstatement as found in imaging studies might also reflect postretrieval processes that operate on the products of retrieval and are thus a consequence rather than a precondition of remembering. Here, we used frequency entrainment as a novel method of tagging memories in the human electroencephalogram (EEG). Participants studied words presented on flickering backgrounds, entraining a steady-state brain response at either 6 or 10 Hz. We found that these frequency signatures rapidly reemerged during a later memory test when participants successfully recognized a word. An additional behavioral experiment suggested that this reactivation occurs in the absence of conscious memory for the frequencies entrained during study. The findings provide empirical evidence for the role of rapid, likely unconscious memory reactivation during retrieval.
Bisphenol S Disrupts Estradiol-Induced Nongenomic Signaling in a Rat Pituitary Cell Line: Effects on Cell Functions

Background: Bisphenol A (BPA) is a well-known endocrine disruptor that imperfectly mimics the effects of physiologic estrogens via membrane-bound estrogen receptors (mERα, mERβ, and GPER/GPR30), thereby initiating nongenomic signaling. Bisphenol S (BPS) is an alternative to BPA in plastic consumer products and thermal paper. Objective: To characterize the nongenomic activities of BPS, we examined signaling pathways it evoked in GH3/B6/F10 rat pituitary cells alone and together with the physiologic estrogen estradiol (E2). Extracellular signal-regulated kinase (ERK)– and c-Jun-N-terminal kinase (JNK)–specific phosphorylations were examined for their correlation to three functional responses: proliferation, caspase activation, and prolactin (PRL) release. Methods: We detected ERK and JNK phosphorylations by fixed-cell immunoassays, identified the predominant mER initiating the signaling with selective inhibitors, estimated cell numbers by crystal violet assays, measured caspase activity by cleavage of fluorescent caspase substrates, and measured PRL release by radioimmunoassay. Results: BPS phosphoactivated ERK within 2.5 min in a nonmonotonic dose-dependent manner (10–15 to 10–7 M). When combined with 10–9 M E2, the physiologic estrogen’s ERK response was attenuated. BPS could not activate JNK, but it greatly enhanced E2-induced JNK activity. BPS induced cell proliferation at low concentrations (femtomolar to nanomolar), similar to E2. Combinations of both estrogens reduced cell numbers below those of the vehicle control and also activated caspases. Earlier activation of caspase 8 versus caspase 9 demonstrated that BPS initiates apoptosis via the extrinsic pathway, consistent with activation via a membrane receptor. BPS also inhibited rapid (≤ 1 min) E2-induced PRL release. Conclusion: BPS, once considered a safe substitute for BPA, disrupts membrane-initiated E2-induced cell signaling, leading to altered cell proliferation, cell death, and PRL release.
Parallel active contour with Lattice Boltzmann scheme on modern GPU

Solving the level set equation of the geodesic active contour (GAC) model in image segmentation typically requires a large number of complicated calculations. To reduce the computing time, we propose a Lattice Boltzmann (LB) Method based partial differential equation solver for the level set equation. The advantages of the LB method are large time steps (thus less iterations) and easy for parallelization. We derive the formula of LB equation parameters for the GAC model and present an approach of GPU implementation. It is the first GPU implementation of the LB model with re-initialization. We adopt a serious of strategies on GPU memory usage considering the Fermi GPU memory hierarchy to further optimize the performance. Experimental results demonstrated that our parallel LB-GAC method achieves a maximal 500+ speedup over previous serial methods with the same segmentation precision.
Wilsonian Effective Actions and the IR/UV Mixing in Noncommutative Gauge Theories

Using background field perturbation theory we study Wilsonian effective actions of noncommutative gauge theories with an arbitrary matter content. We determine the Wilsonian coupling constant and the gauge boson polarization tensor as functions of the momentum scale k at the one-loop level and study their short-distance behaviour as theta k ->0, where theta is the noncommutativity parameter. The mixing between the short-distance and the long-distance degrees of freedom characteristic of noncommutative field theories violates the universality of the Wilsonian action and leads to IR-singularities. We find, in agreement with known results, that the quadratic IR divergencies cancel in supersymmetric gauge theories. The logarithmic divergencies disappear in mass-deformed N=4 theories, but not in other finite N=2 theories. We next concentrate on finite N=2 and mass-deformed N=4 supersymmetric U(1) gauge theories with massive hypermultiplets. The Wilsonian running coupling exhibits a non-trivial threshold behaviour at and well below the noncomutativity scale, eventually becoming flat in the extreme infrared in N=4 theories, but not in N=2 theories. This is interpreted as the (non)-existence of a non-singular commutative limit where the theory is described by a commutative N=2 pure U(1) theory. We expect that our analysis of finite theories is exact to all orders in perturbation theory.
Influential Community Search in Large Networks

Community search is a problem of finding densely connected subgraphs that satisfy the query conditions in a network, which has attracted much attention in recent years. However, all the previous studies on community search do not consider the influence of a community. In this paper, we introduce a novel community model called k-influential community based on the concept of k-core, which can capture the influence of a community. Based on the new community model, we propose a linear-time online search algorithm to find the top-r k-influential communities in a network. To further speed up the influential community search algorithm, we devise a linear-space index structure which supports efficient search of the top-r k-influential communities in optimal time. We also propose an efficient algorithm to maintain the index when the network is frequently updated. We conduct extensive experiments on 7 real-world large networks, and the results demonstrate the efficiency and effectiveness of the proposed methods.
Genetic and Molecular Epidemiological Characterization of a Novel Adenovirus in Antarctic Penguins Collected between 2008 and 2013

Antarctica is considered a relatively uncontaminated region with regard to the infectious diseases because of its extreme environment, and isolated geography. For the genetic characterization and molecular epidemiology of the newly found penguin adenovirus in Antarctica, entire genome sequencing and annual survey of penguin adenovirus were conducted. The entire genome sequences of penguin adenoviruses were completed for two Chinstrap penguins (Pygoscelis antarctica) and two Gentoo penguins (Pygoscelis papua). The whole genome lengths and G+C content of penguin adenoviruses were found to be 24,630–24,662 bp and 35.5–35.6%, respectively. Notably, the presence of putative sialidase gene was not identified in penguin adenoviruses by Rapid Amplification of cDNA Ends (RACE-PCR) as well as consensus specific PCR. The penguin adenoviruses were demonstrated to be a new species within the genus Siadenovirus, with a distance of 29.9–39.3% (amino acid, 32.1–47.9%) in DNA polymerase gene, and showed the closest relationship with turkey adenovirus 3 (TAdV-3) in phylogenetic analysis. During the 2008–2013 study period, the penguin adenoviruses were annually detected in 22 of 78 penguins (28.2%), and the molecular epidemiological study of the penguin adenovirus indicates a predominant infection in Chinstrap penguin population (12/30, 40%). Interestingly, the genome of penguin adenovirus could be detected in several internal samples, except the lymph node and brain. In conclusion, an analysis of the entire adenoviral genomes from Antarctic penguins was conducted, and the penguin adenoviruses, containing unique genetic character, were identified as a new species within the genus Siadenovirus. Moreover, it was annually detected in Antarctic penguins, suggesting its circulation within the penguin population.
Improving Patent Translation using Bilingual Term Extraction and Re-tokenization for Chinese–Japanese

Unlike European languages, many Asian languages like Chinese and Japanese do not have typographic boundaries in written system. Word segmentation (tokenization) that break sentences down into individual words (tokens) is normally treated as the first step for machine translation (MT). For Chinese and Japanese, different rules and segmentation tools lead different segmentation results in different level of granularity between Chinese and Japanese. To improve the translation accuracy, we adjust and balance the granularity of segmentation results around terms for Chinese–Japanese patent corpus for training translation model. In this paper, we describe a statistical machine translation (SMT) system which is built on re-tokenized Chinese-Japanese patent training corpus using extracted bilingual multi-word terms.
MMP-20 mutation in autosomal recessive pigmented hypomaturation amelogenesis imperfecta

During mammalian tooth formation, two proteinases are secreted by ameloblasts: enamelysin (MMP-20) and kallikrein-4 (KLK4). Enamelysin is the early protease. It is expressed by ameloblasts throughout the secretory stage and part of the maturation stage.1–3 KLK4 is the late protease; its expression by ameloblasts begins in the transition stage and continues throughout enamel maturation.4,5 Expression of these two proteases overlaps during the transition and early maturation stages, when the bulk of the organic matrix component is removed from the enamel layer. Because of its early pattern of expression, its ability to generate the same pattern of amelogenin cleavages in vitro as those observed in vivo,6 and the nature of the dental phenotype in enamelysin knockout mice,7 MMP-20 cleavages are thought to play important roles in crystal elongation, proper formation of the dentino–enamel junction (DEJ), and in the maintenance of enamel rod organisation. The extracellular protein KLK4 is believed to be the predominant degradative enzyme that clears enamel proteins from the matrix during the maturation stage.8,9,10 There are a number of recent reviews in the literature on the roles of proteolytic enzymes in dental enamel formation.11–14 Enamelysin is a matrix metalloproteinase (MMP). In humans, enamelysin is expressed from a gene on chromosome 11q22.3-q23 having 10 exons (all coding). 15 The enamelysin protein has 483 amino acids, including the signal peptide, and folds into propeptide, catalytic, linker, and hemopexin domains.16 The active protease migrates as a doublet at 46 and 41 kDa on zymograms.17,18 Its only post-translational modification is a disulphide bridge connecting the first and last amino acids of the hemopexin domain.19 Inherited enamel malformations show a variety of phenotypes that are grouped according to the thickness and hardness of the enamel layer and are described …
High-resolution fiber optic microscopy with fluorescent contrast enhancement for the identification of axillary lymph node metastases in breast cancer: a pilot study

This prospective pilot study evaluates the potential of high-resolution fiber optic microscopy (HRFM) to identify lymph node metastases in breast cancer patients. 43 lymph nodes were collected from 14 consenting breast cancer patients. Proflavine dye was topically applied to lymph nodes ex vivo to allow visualization of nuclei. 242 images were collected at 105 sites with confirmed histopathologic diagnosis. Quantitative statistical features were calculated from images, assessed with one-way ANOVA, and were used to develop a classification algorithm with the goal of objectively discriminating between normal and metastatic tissue. A classification algorithm using mean image intensity and skewness achieved sensitivity of 79% (27/34) and specificity of 77% (55/71). This study demonstrates the technical feasibility and diagnostic potential of HRFM with fluorescent contrast in the ex vivo evaluation of lymph nodes from breast cancer patients.
The Development of a Tool for the Air Data System Calibration Flight Tests Campaign Using Image Processing

The first Flight Test Campaign (FTC) carried out for an experimental aircraft is the calibration of its Air Data System (ADS). In this case, the altitude and airspeed measurements of the aircraft are provided by both anemometric along with the Flight Tests Instrumentation (FTI) systems that are corrupted by installation errors. Therefore, a tool was developed using techniques such as image processing in order to minimize these errors. A tool is described for detecting the position of the aircraft during a FTC through a video of the high-speed camera. The tool detects the aircraft and reference points, calculates altitude and airspeed of the aircraft and determines validity of test point in FTC. The preliminary tests of this tool showed satisfactory results compared to the current method. This paper will discuss such scenario, its preliminary development and the results through performed flights with EMBRAER Jet XAT-26 aircraft and HELIBRAS HB-350L-1 helicopter.
Synthesis and Characterization of a New Al3+-Selective Probe Based on Benzoyl Hydrazine Derivative

A new ‘off-on’ type Al-selective fluorescent probe derived from benzoyl hydrazine has been synthesized and characterized. This probe shows high selectivity towards Al compared to other common metal ions, and complexing with Al triggers a new bond at 450 nm. With optimized conditions, the probe gives a linear response of 8.9×10–9.0 ×10M with a detection limit of 2.9×10 M Al in ethanol. Key-Words:Benzoyl hydrazine derivative, Al, Fluorescent probe, Schiff base.
REFERENCE-BASED STOCHASTIC SUBSPACE IDENTIFICATION FOR OUTPUT-ONLY MODAL ANALYSIS

Abstract When performing vibration tests on civil engineering structures, it is often unpractical and expensive to use artificial excitation (shakers, drop weights). Ambient excitation on the contrary is freely available (traffic, wind), but it causes other challenges. The ambient input remains unknown and the system identification algorithms have to deal with output-only measurements. For instance, realisation algorithms can be used: originally formulated for impulse responses they were easily extended to output covariances. More recently, data-driven stochastic subspace algorithms which avoid the computation of the output covariances were developed. The key element of these algorithms is the projection of the row space of the future outputs into the row space of the past outputs. Also typical for ambient testing of large structures is that not all degrees of freedom can be measured at once but that they are divided into several set-ups with overlapping reference sensors. These reference sensors are needed to obtain global mode shapes. In this paper, a novel approach of stochastic subspace identification is presented that incorporates the idea of the reference sensors already in the identification step: the row space of future outputs is projected into the row space of past reference outputs. The algorithm is validated with real vibration data from a steel mast excited by wind load. The price paid for the important gain concerning computational efficiency in the new approach is that the prediction errors for the non-reference channels are higher. The estimates of the eigenfrequencies and damping ratios do not suffer from this fact.
A new method to estimate ionospheric electric fields and currents using data from a local ground magnetometer network

Abstract. In this study we present a new method to estimate ionospheric electric fields and currents using ground magnetic recordings and measured or modeled ionospheric electric conductivity as the input data. This problem has been studied extensively in the past, and the standard analysis technique for such a set of input parameters is known as the KRM method (Kamide et al., 1981). The new method presented in this study makes use of the same input data as the traditional KRM method, but differs significantly from it in the mathematical approach that is used. In the KRM method one tries to find such a potential electric field, that the resulting current system has the same curl as the ionospheric equivalent currents. In the new method we take a different approach, so that we determine such a curl-free current system that, together with the equivalent currents, it is consistent with a potential electric field. This approach results in a slightly different equation, that makes better use of the information contained in the equivalent currents. In this paper we concentrate on regional studies, where the (unknown) boundary conditions at the borders of the analysis area play a significant role in the KRM solution. In order to overcome this complication, we formulate a novel numerical algorithm to be used with our new calculation method. This algorithm is based on the Cartesian elementary current systems (CECS). With CECS the boundary conditions are implemented in a natural way, making regional studies less prone to errors. We compare the traditional KRM method and our new CECS-based formulation using several realistic models of typical meso-scale phenomena in the auroral ionosphere, including a uniform electrojet, the Ω-bands and the westward traveling surge. It is found that the error in the CECS results is typically about 20%–40%, whereas the errors in the KRM results are significantly larger.