Miracle-dz/UniFAR-FTUs huggingface dataset:
Conserved Roles of CrRLK1L Receptor-Like Kinases in Cell Expansion and Reproduction from Algae to Angiosperms

Receptor-like kinases (RLKs) are regulators of plant development through allowing cells to sense their extracellular environment. They facilitate detection of local endogenous signals, in addition to external biotic and abiotic stimuli. The Catharanthus roseus RLK1-like (CrRLK1L) protein kinase subfamily, which contains FERONIA, plays a central role in regulating fertilization and in cell expansion mechanisms such as cell elongation and tip growth, as well as having indirect links to plant–pathogen interactions. Several components of CrRLK1L signaling pathways have been identified, including an extracellular ligand, coreceptors, and downstream signaling elements. The presence and abundance of the CrRLK1L proteins in the plant kingdom suggest an origin within the Streptophyta lineage, with a notable increase in prevalence in the seeded land plants. Given the function of the sole CrRLK1L protein in a charophycean alga, the possibility of a conserved role in detection and/or regulation of cell wall integrity throughout the Strephtophytes is discussed. Orthologs of signaling pathway components are also present in extant representatives of non-vascular land plants and early vascular land plants including the liverwort Marchantia polymorpha, the moss Physcomitrella patens and the lycophyte Selaginella moellendorffii. Deciphering the roles in development of the CrRLK1L protein kinases in early diverging land plants will provide insights into their ancestral function, furthering our understanding of this diversified subfamily of receptors in higher plants.
DIAGNOSING ERROR PRONE APPLICATION OF OPTIMAL MODEL CALIBRATION

Optimization tools have been developed for automatic calibration of water distribution models. The tools are often based upon a powerful genetic algorithm optimization and seamlessly integrated with hydraulic and water quality modeling systems. It provides the advanced features for engineers and modelers. In spite of the power of the GA modeling, some users report that the optimal calibration tool has not worked effectively for practical model calibration. This paper presents a case study on uncovering the causes of problems in automated calibration and proposes an approach for effectively applying the optimization calibration method. The case study involves a real water distribution system. The model is constructed by experienced modeling engineers and an optimization calibration tool is applied to calibrating the model. However, the initial application of the calibration tool did not make any improvement at all over the uncalibrated model. A detailed analysis has been conducted to diagnose the problems with the model calibration. This study uncovers an error prone application of the optimization-based calibration tool and illustrates effective procedures for applying the calibration tool to a real water distribution model. The procedure and steps have been found efficient at improving model calibration. They may also serve the general guidelines for calibrating water distribution models even without use of optimization.
Investigation of a reliability prevention model for remanufactured systems in automotive

If safety related systems are remanufactured, as for example steering systems, the functionality, the functional safety, the reliability and the quality have to fulfill the series standards such as the E/E/PE standard IEC 61508 or the automobile standard ISO 26262. This paper examines an investigation with the objective to present a prevention model with which the reliability and the renewal function of safety components for remanufactured systems can predict. Failure data serve as a basis and make the predict model not only to a theoretical, but also to a practical tool.
Task Related and Spatially Regularized Common Spatial Patterns for Brain Computer Interfaces

In this study, a novel regularized common spatial pattern method is introduced. Spatial ltering is an important processing step for feature extraction in motor imagery based brain computer interfaces. Common Spatial Patterns (CSP) method is an eective spatial lter for discriminating dierent motor imagery signals acquired using large number of EEG electrodes. Unfortunately, CSP method is sensitive to nonstationery sources like artefacts and noise, which cause overtting. In the literature, some regularization methods developed in order to avert overtting and generate lters that are less sensitive to noise. In this study, we present a method that regularizes CSP lters by taking care of physiological sources of executed motor imagery tasks and spatial rela- tions between electrodes. We compared our method to well known CSP methods on a publicly available EEG dataset by calculating classify- ing performances and analyzing the eect of regularizing CSP visually. Results show that proposed method gives the best overall performance among six CSP methods.
On the use of temporal series of L-and X-band SAR data for soil moisture retrieval. Capitanata plain case study

Abstract This paper investigates the use of time series of ALOS/PALSAR-1 and COSMO-SkyMed data for the soil moisture retrieval (mv) by means of the SMOSAR algorithm. The application context is the exploitation of mv maps at a moderate spatial and temporal resolution for improving flood/drought monitoring at regional scale. The SAR data were acquired over the Capitanata plain in Southern Italy, over which ground campaigns were carried out in 2007, 2010 and 2011. The analysis shows that the mv retrieval accuracy is 5%-7% m3/m3 at L-and X band, although the latter is restricted to a use over nearly bare soil only.
Implementing Remote Presence Using Quadcopter Control by a Non-Invasive BCI Device

Extracting neural signals to control a quadcopter using wireless manner is proposed in this paper for hands-free, silence and effortless human-mobile interaction with remote presence. The brain activity is recorded in real-time and discovered patterns to relate it to facial-expression states with a cheap off-the-shelf electroencephalogram (EEG) headset-Emotic Epoc device. A tablet based mobile framework with Android system is developed to convert these discovered patterns into commands to drive the quadcopter-AR Drone 2.0 through wireless interface. First, neural signals are sequentially extracted from headset and transmitted to the tablet mobile system. In the tablet mobile system, large number of feature vector of EEG can be reduced by using Principle Component Analysis (PCA) to recognize the facial expression to generate suitable commands and driving the quadcopter through wireless interface. Finally, the quadcopter can fly smoothly in accordance with the commands converted by the EEG signals. The experimental results show that the proposed system can easily control quadcopters.
Security Protocols : Principles and Calculi Tutorial

This paper is a basic introduction to some of the main themes in the design and analysis of security protocols. It includes a brief explanation of the principles of protocol design and of a formalism for protocol analysis. It is intended as a written counterpart to a tutorial given at the 2006 International School on Foundations of Security Analysis and Design.
Control-aware mapping of human motion data with stepping for humanoid robots

This paper presents a method for mapping captured human motion with stepping to a humanoid model, considering the current state and the controller behavior. The mapping algorithm modifies the joint angle, trunk and center of mass (COM) trajectories so that the motion can be tracked and desired contact states can be achieved. The mapping is performed in two steps. The first step modifies the joint angle and trunk trajectories to adapt to the robot kinematics and actual contact foot positions. The second step uses a predicted center of pressure (COP) to determine if the balance controller can successfully maintain the robot's balance, and if not, modifies the COM trajectory. Unlike most humanoid control work that handles motion synthesis and control separately, our COM trajectory modification is performed based on the behavior of the robot controller. We verify the approach in simulation using a captured Tai-chi motion that involves unstructured contact state changes.
A low-cost miniature 120GHz SiP FMCW/CW radar sensor with software linearization

This paper presents an integrated mixed-signal 120GHz FMCW/CW radar chipset in a 0. 13μm SiGe BiCMOS technology. It features on-chip MMW built-in-self-test (BIST) circuits, a harmonic transceiver, software linearization (SWL) circuits and a digital interface. This chipset has been tested in a low-cost package, where the antennas are integrated. Above 100GHz, our transceiver has achieved state-ofthe-art integration level and receiver linearity, and DC power consumption.
Low frequency noise sources in InAlAs/InGaAs MODFET's

In this work, we present a study of various low-frequency noise (LFN) sources in InAlAs/InGaAs MODFET structures. The contributions of the main noise sources-drain and source contact resistance fluctuations, channel charge fluctuations and gate current noise-are separated by measuring the drain current power noise spectrum on uncompleted, gate free MODFET structures of different channel lengths. A variety of MBE grown structures was investigated: /spl delta/- and uniformly-doped MODFET's: devices with lattice-matched and strained channel. Also experiments were performed on devices with different source and drain ohmic contacts. <<ETX>>
The relationship between asthma and suicidal behaviours: a systematic literature review

Asthma is a highly prevalent chronic condition worldwide, and is particularly common in younger people compared to other chronic conditions. Asthma can result in a number of symptoms that are detrimental to the quality of life of sufferers. The aim of the present systematic literature review was to analyse the existing literature on the relationship between asthma and fatal and nonfatal suicidal behaviours. Articles were retrieved from Scopus, PubMed, ProQuest and Web of Knowledge. We searched for the terms (suicid* OR self-harm) AND (asthma* OR “bronchial hyperreactivity”) published in English-language peer-reviewed journals between 1990 and December 2014. Original research papers providing empirical evidence about the potential link between asthma and suicidal behaviours were included. The initial search identified 746 articles. Specific limiting criteria reduced the number of articles to the 19 articles that were finally included in the systematic review. The review found a potential link between asthma and suicide mortality, ideation and attempts across the age groups. Limitations of the review include the restriction to English-language papers published within the chosen time period, the limited number of papers involving suicide mortality, and the fact that the majority of papers originated from the USA. Systematic literature review suggests potential link between asthma and suicide mortality, ideation and attempts http://ow.ly/Jowfs
Interstitial Carbonic Anhydrase (CA) Activity in Brain Is Attributable to Membrane-Bound CA Type IV

We tested the hypothesis that extracellular membrane-bound carbonic anhydrase (CA) type IV is responsible for the regulation of interstitial pH (pHo) transients in brain. Rat hippocampal slices were incubated in phosphatidylinositol-specific phospholipase C (PI-PLC), which cleaves the link of CA IV to the external face of plasma membranes. Then evoked alkaline pHo shifts were studied in a recording chamber, using pH microelectrodes. Incubation fluid was saved for later analysis. The ability to buffer a rapid alkaline load was reduced markedly in PI-PLC-treated tissue as compared with adjacent, paired control slices. The effect of benzolamide (a poorly permeant CA inhibitor) on evoked pHo shifts was diminished greatly in the PI-PLC-treated tissue, consistent with the washout of interstitial CA. Treatment of the incubation fluid with SDS abolished nearly all of the CA activity in fluid from controls, whereas an SDS-insensitive component remained in the fluid from PI-PLC-treated slices. These data suggested that CA type II (which is blocked by SDS) leaked from injured glial cells in both slice preparations, whereas CA type IV (which is insensitive to SDS) was liberated selectively into the fluid from PI-PLC-treated tissue. Western blot analysis was consistent with this interpretation, demonstrating a predominance of CA IV in the incubation fluid from PI-PLC-treated tissue and variable amounts of CA II in fluid from PI-PLC-treated and control slices. These results demonstrate that interstitial CA activity brain is attributable principally to membrane-bound CA IV.
Effect of passivation on the enhanced low dose rate sensitivity of National LM124 operational amplifiers

This work presents high and low dose rate test results for LM124 operational amplifiers that were fabricated with six passivation layer types. Consistent with previous data, these results confirm that passivation layers play a significant role in determining ELDRS response. SIMS analysis suggests that an influential factor in determining the high and low dose rate response may be the location and concentration of hydrogen at the Si-SiO/sub 2/ interface and in the passivation layers.
Do Non-Strategic Sanctions Obey the Law of Demand? The Demand for Punishment in the Voluntary Contribution Mechanism

The prospect of receiving a monetary sanction for free riding has been shown to increase contributions to public goods. We ask whether the impulse to punish is unresponsive to the cost to the punisher, or whether, like other preferences, it interacts with prices to generate a conventional demand curve. We test the price responsiveness of the demand for punishment by randomly varying the cost of reducing the earnings of other group members following laboratory voluntary contribution decisions. In our design, new groups are formed after each interaction and no subject faces any other more than once, so there is no strategic reason to punish. We nonetheless find significant levels of punishment, and we learn that both price and the extent to which the recipient's contribution is below the group mean are significant determinants of the quantity of punishment demanded. Moreover, punishment is mainly directed at free riders even when it costs nothing to the punisher. However, the propensity to punish egregious free riding varies considerably within our subject pool, from non-punishers to aggressive punishers.
Membrane filter method to study the effects of Lactobacillus acidophilus and Bifidobacterium longum on fecal microbiota

A large number of commensal bacteria inhabit the intestinal tract, and interbacterial communication among gut microbiota is thought to occur. In order to analyze symbiotic relationships between probiotic strains and the gut microbiota, a ring with a membrane filter fitted to the bottom was used for in vitro investigations. Test strains comprising probiotic nitto strains (Lactobacillus acidophilus NT and Bifidobacterium longum NT) and type strains (L. acidophilus JCM1132T and B. longum JCM1217T) were obtained from diluted fecal samples using the membrane filter to simulate interbacterial communication. Bifidobacterium spp. , Streptococcus pasteurianus, Collinsella aerofaciens, and Clostridium spp. were the most abundant gut bacteria detected before coculture with the test strains. Results of the coculture experiments indicated that the test strains significantly promote the growth of Ruminococcus gnavus, Ruminococcus torques, and Veillonella spp. and inhibit the growth of Sutterella wadsworthensis. Differences in the relative abundances of gut bacterial strains were furthermore observed after coculture of the fecal samples with each test strain. Bifidobacterium spp. , which was detected as the dominant strain in the fecal samples, was found to be unaffected by coculture with the test strains. In the present study, interbacterial communication using bacterial metabolites between the test strains and the gut microbiota was demonstrated by the coculture technique. The detailed mechanisms and effects of the complex interbacterial communications that occur among the gut microbiota are, however, still unclear. Further investigation of these relationships by coculture of several fecal samples with probiotic strains is urgently required.
Functional Network Identification in Human Resting-state fMRI using Hierarchical Clustering by Time-Lagged Correlations

Mapping of human resting-state functional network through functional magnetic resonance imaging (fMRI) have been proli c in recent years congruent with the maturing of Blood Oxygen Level Dependent (BOLD) imaging. Whereas focus have been maintained upon advancing the complexity of the models with model-free clustering approaches and methods using spectral decomposition, relatively few works have been concentrating on the temporal dimension of fMRI data. Specially lacking is models which include temporal lag of fMRI time series explicitly into account. In this investigation, a framework was developed to map human resting-state functional networks with a model which includes temporal lag. Time-lagged cross correlations and maximum delay times were used as a basis for the construction of distance measures used for hierarchical clustering. The delay maps generated when calculating the cross correlations give preliminary indication that the zero-lag assumption of many current models may be lacking in various aspects. The resulting clusters are spatially noisy, which was expected since the distance measure used do not hold spatial information explicitly. However, multiple structures could be identi ed from the resulting clusters which strengthens causality between BOLD signal correlations and functional networks. There are signi cant di erences between the clusters from the time-lagged correlation distances and their zero lag counterparts. While the distance maps are signi cantly di erent in visualization, some structures may be found in both while some are only identi able in one. It is concluded that time-lagged correlations could be a useful distance measure in identifying functional networks and structures which could not be identi ed when assuming zero lag. Identi kation av mänsklig funktionella nätverk i vila hos fMRI med hierarkisk gruppering med tidsfördröjda korrelationer
Improved Estimation of Normalizing Constants From Markov Chain Monte Carlo Output

Normalizing constants of conditional distributions include Bayesian marginal likelihoods and likelihoods of mixture models, such as hierarchical models and state-space time-series models. A promising method for estimating such quantities was proposed by Chib and Jeliazkov (CJ) and improved by Mira and Nicholls using bridge sampling results. Here three additional improvements and one theoretical result for the methods of CJ are given. First, a different Metropolis–Hastings proposal density is used for estimating the normalizing constant than for the MCMC run. Second, a ratio of effective sample sizes is incorporated into the optimal bridge function to account for sequential dependence of the MCMC output. Third, the Moving Block Bootstrap is used to estimate the variance of the normalizing constant estimates, which is then minimized with respect to the CJ proposal density and bridge function. It is shown that the optimal proposal density for estimating the normalizing constant, regardless of the proposal de.
Least Common Ancestor Based Method for Efficiently Constructing Rooted Supertrees

Phylogenetic supertree is a collection of different phylogenetic trees combined into a single tree forming a tree of life. The smaller overlapping phylogenetic trees are combined in such a way that no branching information is lost. This problem is important for several biological applications. Yet the solution is difficult as exponentially large number of supertrees exists for a given set of trees and the optimal tree has to be selected based upon some optimality criteria. In this paper, we propose a polynomial time algorithm for combining phylogenetic trees, which makes use of least common ancestor information as optimality criterion. The algorithm satisfies the desirable properties of a phylogenetic supertree method as mentioned in literature, and constructs a single phylogenetic supertree even for incompatible input trees which is difficult to solve. Experimental results and comparisons with other works show the superiority of our algorithm.
Draco: Efficient Resource Management for Resource-Constrained Control Tasks

In many application areas, including control systems, careful management of system resources is key to providing the best application performance. Traditional control systems with multiple control loops statically allocate a fixed portion of the system resources to each controller based on their average or worst-case resource requirements. However, controllers' resource needs vary depending on the jobs they perform and the state of the systems they control. A controller of a plant operating close to its equilibrium requires fewer resources than a controller of a plant operating far from its equilibrium point. The Draco dynamic rate control system exploits this fact by dynamically allocating resources to control systems based on system state. Our research demonstrates that Draco provides significantly better overall control performance with much less resources than static controllers. Our experimental evaluation shows that in the control scenarios we examined Draco provides up to 25 percent better control performance with 30 percent less resources.
A genome-wide association study for myopia and refractive error identifies a susceptibility locus at 15 q 25

Myopia and hyperopia are at opposite ends of the continuum of refraction, the measure of the eye′s ability to focus light, which is an important cause of visual impairment (when aberrant) and is a highly heritable trait. We conducted a genome-wide association study for refractive error in 4,270 individuals from the TwinsUK cohort. We identified SNPs on 15q25 associated with refractive error (rs8027411, P = 7.91 × 10−8). We replicated this association in six adult cohorts of European ancestry with a combined 13,414 individuals (combined P = 2.07 × 10−9). This locus overlaps the transcription initiation site of RASGRF1, which is highly expressed in neurons and retina and has previously been implicated in retinal function and memory consolidation. Rasgrf1−/− mice show a heavier average crystalline lens (P = 0.001). The identification of a susceptibility locus for refractive error on 15q25 will be important in characterizing the molecular mechanism responsible for the most common cause of visual impairment.
Carl Edward Rasmussen and Marc Peter Deisenroth Probabilistic Inference for Fast Learning in Control Chapter in Recent Advances in Reinforcement Learning , Lecture

We provide a novel framework for very fast model-based reinforcement learning in continuous state and action spaces. The framework requires probabilistic models that explicitly characterize their levels of confidence. Within this framework, we use flexible, non-parametric models to describe the world based on previously collected experience. We demonstrate learning on the cart-pole problem in a setting where we provide very limited prior knowledge about the task. Learning progresses rapidly, and a good policy is found after only a hand-full of iterations.