Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimisation of corpus-derived probabilistic grammars

This paper examines the usefulness of corpus-derived probabilistic grammars as a basis for the automatic construction of grammars optimised for a given parsing task. Initially, a probabilistic context-free grammar (PCFG) is derived by a straightforward derivation technique from the Wall Street Journal (WSJ) Corpus, and a baseline is established by testing the resulting grammar on four different parsing tasks. In the first optimisation step, different kinds of local structural context (LSC) are incorporated into the basic PCFG. Improved parsing results demonstrate the usefulness of the added structural context information. In the second optimisation step, LSC-PCFGs are optimised in terms of grammar size and performance for a given parsing task. Tests show that significant improvements can be achieved by the method proposed. The structure of this paper is as follows. Section 2 discusses the practica
Development of a six station knee wear simulator and preliminary wear results

Abstract In order to assess the wear performance of different designs of total knee replacements (TKR), a six station multi-axis knee simulator has been designed, built and commissioned. The most important features of a knee simulator are representative angles of flexion-extension synchronized with a dynamically applied load, and a combination of rolling and sliding motion. The simulator typically applies flexion-extension of 0-65°, anterior-posterior translation of up to 15 mm, a dynamic load of up to 5.0 kN, and operates at 1.0 Hz. The loads and motions are applied using computer controlled servohydraulic actuators and hence their profiles are easily modified. A preliminary wear test has been conducted using a Kinemax (Howmedica, United Kingdom) TKR. The test was conducted in 30 per cent bovine serum which was changed every 150 000 cycles, at which time the bearing surfaces were examined and the UHMWPE tibial component was weighed. Over eight million cycles, a tibial wear rate of 2.62 mg/106 cycles was measured. The mild wear observed was characterized by burnishing and slight scratching in the anterior-posterior direction. These observations are broadly in line with both in vitro and ex vivo studies reported in the literature for this type of prosthesis. Delamination wear sometimes observed in vivo was not seen.
Accurate Quantification of Lipid Species by Electrospray Ionization Mass Spectrometry — Meets a Key Challenge in Lipidomics

Electrospray ionization mass spectrometry (ESI-MS) has become one of the most popular and powerful technologies to identify and quantify individual lipid species in lipidomics. Meanwhile, quantitative analysis of lipid species by ESI-MS has also become a major obstacle to meet the challenges of lipidomics. Herein, we discuss the principles, advantages, and possible limitations of different mass spectrometry-based methodologies for lipid quantification, as well as a few practical issues important for accurate quantification of individual lipid species. Accordingly, accurate quantification of individual lipid species, one of the key challenges in lipidomics, can be practically met.
Real-Time Control of a Two-Wheeled Inverted Pendulum Mobile Robot

The research on two-wheeled inverted pendulum (T- WIP) mobile robots or commonly known as balancing robots have gained momentum over the last decade in a number of robotic laboratories around the world. This paper describes the hardware design of such a robot. The objective of the design is to develop a T- WIP mobile robot as well as MATLAB interfacing configuration to be used as flexible platform comprises of embedded unstable linear plant intended for research and teaching purposes. Issues such as selection of actuators and sensors, signal processing units, MATLAB Real Time Workshop coding, modeling and control scheme will be addressed and discussed. The system is then tested using a well- known state feedback controller to verify its functionality. Keywords—Embedded System, Two-wheeled Inverted Pendulum Mobile Robot.
Motion Planning Under Uncertainty for Image-guided Medical Needle Steering

We develop a new motion planning algorithm for a variant of a Dubins car with binary left/right steering and apply it to steerable needles, a new class of flexible bevel-tip medical needle that physicians can steer through soft tissue to reach clinical targets inaccessible to traditional stiff needles. Our method explicitly considers uncertainty in needle motion due to patient differences and the difficulty in predicting needle/tissue interaction. The planner computes optimal steering actions to maximize the probability that the needle will reach the desired target. Given a medical image with segmented obstacles and target, our method formulates the planning problem as a Markov decision process based on an efficient discretization of the state space, models motion uncertainty using probability distributions and computes optimal steering actions using dynamic programming. This approach only requires parameters that can be directly extracted from images, allows fast computation of the optimal needle entry point and enables intra-operative optimal steering of the needle using the pre-computed dynamic programming look-up table. We apply the method to generate motion plans for steerable needles to reach targets inaccessible to stiff needles, and we illustrate the importance of considering uncertainty during motion plan optimization.
Impact of soil moisture on dust outbreaks in East Asia: Using satellite and assimilation data

This study is the first assessment of the effects of soil moisture on dust outbreaks using satellite‐derived aerosol optical depth (AOD) and global assimilation data on the sand regions across East Asia. The relationships among dust outbreaks, soil moisture, and wind speed were estimated using data sets of the Moderate Resolution Imaging Spectroradiometer and Global Land Data Assimilation System collected over 11 years (2003–2013). The mean AOD exponentially decreased with increasing soil moisture under different wind speed conditions (average determination coefficient = 0.95). As the wind speed conditions became stronger, the probability of a dust outbreak became greatly affected by soil moisture. The threshold soil moisture for dust outbreaks increased with increasing wind speed and decreased with increasing dust‐outbreak criteria of AOD. Our results have the capability to be applied to satellite‐based dust‐outbreak prediction and global‐scale dust‐emission studies.
Antibody-induced uncoating of human rhinovirus B14

Significance Rhinoviruses (RVs) frequently cause respiratory infections in humans. However, there are currently no approved antiviral treatments or vaccines available. Using cryo-electron microscopy (cryo-EM), we have shown that the antigen-binding fragment of a neutralizing antibody, C5, binds to RV-B14 and causes significant structural rearrangements of the capsid to allow release of the viral genome. C5-induced virus uncoating depends upon temperature and virus–Fab molar ratio. These results present so far the highest resolution cryo-EM structures of a virus–antibody complex and suggest a conserved mechanism whereby antibodies neutralize infections by RVs and related viruses via induction of premature genome release from the capsid. Rhinoviruses (RVs) are the major causes of common colds in humans. They have a nonenveloped, icosahedral capsid surrounding a positive-strand RNA genome. Here we report that the antigen-binding (Fab) fragment of a neutralizing antibody (C5) can trigger genome release from RV-B14 to form emptied particles and neutralize virus infection. Using cryo-electron microscopy, structures of the C5 Fab in complex with the full and emptied particles have been determined at 2.3 Å and 3.0 Å resolution, respectively. Each of the 60 Fab molecules binds primarily to a region on viral protein 3 (VP3). Binding of the C5 Fabs to RV-B14 results in significant conformational changes around holes in the capsid through which the viral RNA might exit. These results are so far the highest resolution view of an antibody–virus complex and elucidate a mechanism whereby antibodies neutralize RVs and related viruses by inducing virus uncoating.
ASimplifiedNeuronalModel for the Instigation and Propagation of Cortical Spreading Depression

In this paper, we construct a simplified neuronal model that is capable of simulating the instigation of cortical spreading depression (CSD) and propagation of a CSD wave. Our model is a simplification and extension of a single neuron model proposed in the literature for studying the instigation of CSD. Using the simplified neuronal model, we construct a network of these simplified neurons. This network model shows that the propagation of a CSD wave occurs naturally after it is instigated electrically or chemically. Although the model is simple, the speed of the CSD wave predicted by our model is consistent with experimentally observed values. Finally, our model allows us to investigate the effects of specific ion channels on the spread of a CSD wave. AMS subject classifications: 34A33, 34A34, 92C20, 92C42, 97M60
The Role of Amino Acid Permeases and Tryptophan Biosynthesis in Cryptococcus neoformans Survival

Metabolic diversity is an important factor during microbial adaptation to different environments. Among metabolic processes, amino acid biosynthesis has been demonstrated to be relevant for survival for many microbial pathogens, whereas the association between pathogenesis and amino acid uptake and recycling are less well-established. Cryptococcus neoformans is an opportunistic fungal pathogen with many habitats. As a result, it faces frequent metabolic shifts and challenges during its life cycle. Here we studied the C. neoformans tryptophan biosynthetic pathway and found that the pathway is essential. RNAi indicated that interruptions in the biosynthetic pathway render strains inviable. However, auxotroph complementation can be partially achieved by tryptophan uptake when a non preferred nitrogen source and lower growth temperature are applied, suggesting that amino acid permeases may be the target of nitrogen catabolism repression (NCR). We used bioinformatics to search for amino acid permeases in the C. neoformans and found eight potential global permeases (AAP1 to AAP8). The transcriptional profile of them revealed that they are subjected to regulatory mechanisms which are known to respond to nutritional status in other fungi, such as (i) quality of nitrogen (Nitrogen Catabolism Repression, NCR) and carbon sources (Carbon Catabolism Repression, CCR), (ii) amino acid availability in the extracellular environment (SPS-sensing) and (iii) nutritional deprivation (Global Amino Acid Control, GAAC). This study shows that C. neoformans has fewer amino acid permeases than other model yeasts, and that these proteins may be subjected to complex regulatory mechanisms. Our data suggest that the C. neoformans tryptophan biosynthetic pathway is an excellent pharmacological target. Furthermore, inhibitors of this pathway cause Cryptococcus growth arrest in vitro.
Near-to-Far Self-Supervised Road Estimation for Complicated Environments

Abstract In this paper, we propose a novel approach to stable near and long range perception for various complex outdoor environments. Our techniques cope robustly with near-range road estimation using a laser scanner and long-range terrain classification using a color camera. Near-range road surface conditions are estimated by using information of remission value as reflectivity of a laser. We apply graph cut algorithm to grid map in order to estimate road region robustly also in complex environments where fallen leaves exist sparsely. Moreover, we propose superpixel-based terrain classification method which can give a good performance compared with pixel-based classification. Our approach has real-time processing. Experimental results have shown that demonstrate a marked increase in long-range classification and near-range road estimation accuracy over standard methods.
Sumoylation of eIF4A2 affects stress granule formation

ABSTRACT Regulation of protein synthesis is crucial for cells to maintain viability and to prevent unscheduled proliferation that could lead to tumorigenesis. Exposure to stress results in stalling of translation, with many translation initiation factors, ribosomal subunits and mRNAs being sequestered into stress granules or P bodies. This allows the re-programming of the translation machinery. Many aspects of translation are regulated by post-translational modification. Several proteomic screens have identified translation initiation factors as targets for sumoylation, although in many cases the role of this modification has not been determined. We show here that eIF4A2 is modified by SUMO, with sumoylation occurring on a single residue (K226). We demonstrate that sumoylation of eIF4A2 is modestly increased in response to arsenite and ionising radiation, but decreases in response to heat shock or hippuristanol. In arsenite-treated cells, but not in hippuristanol-treated cells, eIF4A2 is recruited to stress granules, suggesting sumoylation of eIF4A2 correlates with its recruitment to stress granules. Furthermore, we demonstrate that the inability to sumoylate eIF4A2 results in impaired stress granule formation, indicating a new role for sumoylation in the stress response. Summary: In response to stress, proteins required to initiate protein synthesis are modified; we demonstrate that sumoylation of eIF4A2 correlates with its recruitment to stress granules.
How good is bargained routing?

Game theoretic models have been widely employed in many networking contexts. Research to date has mainly focused on non-cooperative networking games, where the selfish agents cannot reach a binding agreement on the way they would share the network infrastructure and the operating points are the Nash equilibria. These are typically inefficient, as manifested by large values of the Price of Anarchy (PoA). Many approaches have been proposed for mitigating this problem, however under the standing assumption of a non-cooperative game. In a growing number of networking scenarios it is possible for the selfish agents to communicate and reach an agreement, i.e., play a cooperative game. Therefore, the degradation of performance should be considered at an operating point that is a cooperative game solution. Accordingly, our goal is to lay foundations for the application of cooperative game theory to fundamental problems in networking. We explain our choice of the Nash Bargaining Scheme (NBS) as the solution concept, and we introduce the Price of Selfishness (PoS), which considers the degradation of performance at an NBS. We focus on the fundamental load balancing game of routing over parallel links. First, we study the classical scenario of agents that consider the same performance objectives. While the PoA here can be very large, we establish that, under plausible assumptions, the PoS attains its minimum value, i.e., through bargaining, the selfish agents reach social optimality. We then extend our study to consider the “heterogeneous” case, where agents may consider vastly different performance objectives. We demonstrate that the PoS and PoA can be unbounded, yet we explain why both measures may now be unsuitable. Accordingly, we introduce the Price of Heterogeneity (PoH), as a proper extension of the PoA. We establish an upper-bound on the PoH for a general class of heterogeneous performance objectives, and indicate that it provides incentives for bargaining also in this general case. We discuss network design guidelines that follow from our findings.
Development of the mesencephalic dopaminergic neuron system is compromised in the absence of neurogenin 2

Neurogenin 2 (Ngn2) is a proneural gene involved in neuronal differentiation and subtype specification in various regions of the nervous system. In the ventral midbrain, Ngn2 is expressed in a spatiotemporal pattern that correlates with the generation of mesencephalic dopaminergic (mesDA) neurons. We show here that lack of Ngn2 impairs the development of mesDA neurons, such that less than half of the normal mesDA neuron number remain in Ngn2 mutant mice at postnatal stages. Analysis of Ngn2 mutant mice during mesDA neurogenesis show that medially located precursors are formed but are arrested in their differentiation at a stage when they have not yet acquired the characteristics of mesDA neuron precursors. Loss of Ngn2 function appears to specifically affect the generation of DA neurons, as the development of other types of neurons within the ventral midbrain is unaltered. Ngn2 is the first example of a gene expressed in progenitors in the ventricular zone of the mesDA neuron domain that is essential for proper mesDA neuron differentiation, and whose loss of function causes impaired mesDA neurogenesis without other major abnormalities in the ventral midbrain.
Arctic patterned-ground ecosystems: A synthesis of field studies and models along a North American Arctic Transect

Arctic landscapes have visually striking patterns of small polygons, circles, and hummocks. The linkages between the geophysical and biological components of these systems and their responses to climate changes are not well understood. The "Biocomplexity of Patterned Ground Ecosystems" project examined patterned-ground features (PGFs) in all five Arctic bioclimate subzones along an 1800-km trans-Arctic temperature gradient in northern Alaska and northwestern Canada. This paper provides an overview of the transect to illustrate the trends in climate, PGFs, vegetation, n-factors, soils, active-layer depth, and frost heave along the climate gradient. We emphasize the thermal effects of the vegetation and snow on the heat and water fluxes within patterned-ground systems. Four new modeling approaches build on the theme that vegetation controls microscale soil temperature differences between the centers and margins of the PGFs, and these in turn drive the movement of water, affect the formation of aggradation ice, promote differential soil heave, and regulate a host of system propel-ties that affect the ability of plants to colonize the centers of these features. We conclude with an examination of the possible effects of a climate wan-ning on patterned-ground ecosystems.
SEL1L Regulates Adhesion, Proliferation and Secretion of Insulin by Affecting Integrin Signaling

SEL1L, a component of the endoplasmic reticulum associated degradation (ERAD) pathway, has been reported to regulate the (i) differentiation of the pancreatic endocrine and exocrine tissue during the second transition of mouse embryonic development, (ii) neural stem cell self-renewal and lineage commitment and (iii) cell cycle progression through regulation of genes related to cell-matrix interaction. Here we show that in the pancreas the expression of SEL1L is developmentally regulated, such that it is readily detected in developing islet cells and in nascent acinar clusters adjacent to basement membranes, and becomes progressively restricted to the islets of Langherans in post-natal life. This peculiar expression pattern and the presence of two inverse RGD motifs in the fibronectin type II domain of SEL1L protein indicate a possible interaction with cell adhesion molecules to regulate islets architecture. Co-immunoprecipitation studies revealed SEL1L and ß1-integrin interaction and, down-modulation of SEL1L in pancreatic ß-cells, negatively influences both cell adhesion on selected matrix components and cell proliferation likely due to altered ERK signaling. Furthermore, the absence of SEL1L protein strongly inhibits glucose-stimulated insulin secretion in isolated mouse pancreatic islets unveiling an important role of SEL1L in insulin trafficking. This phenotype can be rescued by the ectopic expression of the ß1-integrin subunit confirming the close interaction of these two proteins in regulating the cross-talk between extracellular matrix and insulin signalling to create a favourable micro-environment for ß-cell development and function.
Fast performance 3 D object recognition : Dealing with rotationally symmetric objects

In this paper we extend a recent approach for 3D object recognition in order to deal with rotationally symmetric objects. These are frequent in daily environments and can be recognized with significant computational savings if symmetrical features are jointly represented. We show improvements up to 120x with respect to state-of-the-art methods.
Algorithmic skeletons for stream programming in embedded heterogeneous parallel image processing applications

Algorithmic skeletons can be used to write architecture independent programs, shielding application developers from the details of a parallel implementation. In this paper, we present a C-like skeleton implementation language, PEPCI, that uses term rewriting and partial evaluation to specify skeletons for parallel C dialects. By using skeletons to control the iteration of kernel functions, we provide a stream programming language that is better tailored to the user as well as the underlying architecture. Skeleton merging allows us to reduce the overheads usually associated with breaking an application into small kernels. We have implemented an example image processing application on a heterogeneous embedded prototype platform consisting of an SIMD and ILP processor, and show that a significant speedup can be achieved without requiring knowledge of data parallel processing.
Numerical modeling of trace element behavior during crystal settling and reequilibration in high-silica magma bodies

[1] In a magma body, heat loss occurs primarily along the margin. With few exceptions, field evidence and physical models have suggested that most crystallization takes place along the margin during a certain period. In the interior of the body, the melt is generally hotter and chemically less evolved; crystals that settle from the upper part are likely to react with the melt. The high-silica ash flow tuffs erupted instantaneously from zoned magma bodies provide evidence that crystals have sunk and reacted with the surrounding melts. This paper develops a heat and mass transfer model for crystal settling and reequilibration to quantify the trace element behavior in such magma bodies. Previous crystallization models such as fractional and equilibrium crystallization have assumed that a melt with a single composition evolves along a single liquid line of descent with increasing degree of crystallization. In the present model, however, melts of various compositions exist within the body at a given time. In addition, the liquid line of descent itself changes with time. A unique and important feature of the present model is this temporal variation of liquid lines of descent. The chemical evolution expected from crystal settling and reequilibration is consistent with the data from the Bishop Tuff high-silica magma body and might account for some characteristic patterns of chemical zonation observed in high-silica magma bodies.
Clustering by Passing Messages Between Data Points

Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only if that initial choice is close to a good solution. We devised a method called “affinity propagation,” which takes as input measures of similarity between pairs of data points. Real-valued messages are exchanged between data points until a high-quality set of exemplars and corresponding clusters gradually emerges. We used affinity propagation to cluster images of faces, detect genes in microarray data, identify representative sentences in this manuscript, and identify cities that are efficiently accessed by airline travel. Affinity propagation found clusters with much lower error than other methods, and it did so in less than one-hundredth the amount of time.