julilili42/papers huggingface dataset:
Tectonic control on rock uplift, exhumation, and topography above an oceanic ridge collision: Southern Patagonian Andes (47°S), Chile
2016-04-30

The subduction of bathymetric anomalies at convergent margins can profoundly affect subduction dynamics, magmatism, and the structural and geomorphic evolution of the overriding plate. The Northern Patagonian Icefield (NPI) is located east of the Chile Triple Junction at similar to 47 degrees S, where the Chile Rise spreading center collides with South America. This region is characterized by an abrupt increase in summit elevations and relief that has been controversially debated in the context of geodynamic versus glacial erosion effects on topography. Here we present geomorphic, thermochronological, and structural data that document neotectonic activity along hitherto unrecognized faults along the flanks of the NPI. New apatite (U-Th)/He bedrock cooling ages suggest faulting since 2-3 Ma. We infer the northward translation of an similar to 140 km long fore-arc sliver-the NPI block-results from enhanced partitioning of oblique plate convergence due to the closely spaced collision of three successive segments of the Chile Rise. In this model, greater uplift occurs in the hanging wall of the Exploradores thrust at the northern leading edge of the NPI block, whereas the Cachet and Liquine-Ofqui dextral faults decouple the NPI block along its eastern and western flanks, respectively. Localized extension possibly occurs at its southern trailing edge along normal faults associated with margin-parallel extension, tectonic subsidence, and lower elevations along the Andean crest line. Our neotectonic model provides a novel explanation for the abrupt topographic variations inland of the Chile Triple Junction and emphasizes the fundamental effects of local tectonics on exhumation and topographic patterns in this glaciated landscape.
Revisiting hydraulic hysteresis based on long‐term monitoring of hydraulic states in lysimeters
2016-04-30

Abstract Hysteretic processes have been recognized for decades as an important characteristic of soil hydraulic behavior. Several studies confirmed that wetting and drying periods cannot be described by a simple functional relationship, and that some nonequilibrium of the water retention characteristics has to be taken into account. A large number of models describing the hysteresis of the soil water retention characteristic were successfully tested on soil cores under controlled laboratory conditions. However, its relevance under field conditions under natural forcings has rarely been investigated. In practice, the modeling of field soils usually neglects the hysteretic nature of soil hydraulic properties. In this study, long‐term observations of water content and matric potential in lysimeters of the lysimeter network TERENO‐SoilCan are presented, clearly demonstrating the hysteretic behavior of field soils. We propose a classification into three categories related to different time scales. Based on synthetic and long‐term monitoring data, three different models of hysteresis were applied to data sets showing different degrees of hysteresis. We found no single model to be superior to the others. The model ranking depended on the degree of hysteresis. All models were able to reflect the general structure of hysteresis in most cases but failed to reproduce the detailed trajectories of state variables especially under highly transient conditions. As an important result we found that the temporal dynamics of wetting and drying significantly affects these trajectories which should be accounted for in future model concepts.
Modeling Soil Processes: Review, Key Challenges, and New Perspectives
2016-05-01

Core Ideas A community effort is needed to move soil modeling forward. Establishing an international soil modeling consortium is key in this respect. There is a need to better integrate existing knowledge in soil models. Integration of data and models is a key challenge in soil modeling. The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate‐change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.
Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data
2016-05-01

The psychometric function describes how an experimental variable, such as stimulus strength, influences the behaviour of an observer. Estimation of psychometric functions from experimental data plays a central role in fields such as psychophysics, experimental psychology and in the behavioural neurosciences. Experimental data may exhibit substantial overdispersion, which may result from non-stationarity in the behaviour of observers. Here we extend the standard binomial model which is typically used for psychometric function estimation to a beta-binomial model. We show that the use of the beta-binomial model makes it possible to determine accurate credible intervals even in data which exhibit substantial overdispersion. This goes beyond classical measures for overdispersion-goodness-of-fit-which can detect overdispersion but provide no method to do correct inference for overdispersed data. We use Bayesian inference methods for estimating the posterior distribution of the parameters of the psychometric function. Unlike previous Bayesian psychometric inference methods our software implementation-psignifit 4-performs numerical integration of the posterior within automatically determined bounds. This avoids the use of Markov chain Monte Carlo (MCMC) methods typically requiring expert knowledge. Extensive numerical tests show the validity of the approach and we discuss implications of overdispersion for experimental design. A comprehensive MATLAB toolbox implementing the method is freely available; a python implementation providing the basic capabilities is also available.
A Nexus Consisting of Beta-Catenin and Stat3 Attenuates BRAF Inhibitor Efficacy and Mediates Acquired Resistance to Vemurafenib
2016-05-01

Acquired resistance to second generation BRAF inhibitors (BRAFis), like vemurafenib is limiting the benefits of long term targeted therapy for patients with malignant melanomas that harbor BRAF V600 mutations. Since many resistance mechanisms have been described, most of them causing a hyperactivation of the MAPK- or PI3K/AKT signaling pathways, one potential strategy to overcome BRAFi resistance in melanoma cells would be to target important common signaling nodes. Known factors that cause secondary resistance include the overexpression of receptor tyrosine kinases (RTKs), alternative splicing of BRAF or the occurrence of novel mutations in MEK1 or NRAS. In this study we show that β-catenin is stabilized and translocated to the nucleus in approximately half of the melanomas that were analyzed and which developed secondary resistance towards BRAFi. We further demonstrate that β-catenin is involved in the mediation of resistance towards vemurafenib in vitro and in vivo. Unexpectedly, β-catenin acts mainly independent of the TCF/LEF dependent canonical Wnt-signaling pathway in resistance development, which partly explains previous contradictory results about the role of β-catenin in melanoma progression and therapy resistance. We further demonstrate that β-catenin interacts with Stat3 after chronic vemurafenib treatment and both together cooperate in the acquisition and maintenance of resistance towards BRAFi.
The Effects of High Steady State Auxin Levels on Root Cell Elongation in Brachypodium
2016-05-01

The long-standing Acid Growth Theory of plant cell elongation posits that auxin promotes cell elongation by stimulating cell wall acidification and thus expansin action. To date, the paucity of pertinent genetic materials has precluded thorough analysis of the importance of this concept in roots. The recent isolation of mutants of the model grass species Brachypodium distachyon with dramatically enhanced root cell elongation due to increased cellular auxin levels has allowed us to address this question. We found that the primary transcriptomic effect associated with elevated steady state auxin concentration in elongating root cells is upregulation of cell wall remodeling factors, notably expansins, while plant hormone signaling pathways maintain remarkable homeostasis. These changes are specifically accompanied by reduced cell wall arabinogalactan complexity but not by increased proton excretion. On the contrary, we observed a tendency for decreased rather than increased proton extrusion from root elongation zones with higher cellular auxin levels. Moreover, similar to Brachypodium, root cell elongation is, in general, robustly buffered against external pH fluctuation in Arabidopsis thaliana However, forced acidification through artificial proton pump activation inhibits root cell elongation. Thus, the interplay between auxin, proton pump activation, and expansin action may be more flexible in roots than in shoots.
Obstacle detection, tracking and avoidance for a teleoperated UAV
2016-05-01

In this paper, we present a collision-free indoor navigation algorithm for teleoperated multirotor Unmanned Aerial Vehicles (UAVs). Assuming an obstacle rich environment, the algorithm keeps track of detected obstacles in the local surroundings of the robot. The detection part of the algorithm is based on measurements from an RGB-D camera and a Bin-Occupancy filter capable of tracking an unspecified number of targets. We use the estimate of the robot's velocity to update the obstacles state when they leave the direct field of view of the sensor. The avoidance part of the algorithm is based on the Model Predictive Control approach. By predicting the possible future obstacles states, it filters the operator commands to prevent collisions. The method is validated on a platform equipped with its own computational unit, which makes it self-sufficient in terms of external CPUs.
Ambient intimacy on Twitter
2016-05-01

Ambient intimacy refers to a feeling of closeness toward certain others developed mainly by following their status updates on social media. Previous researchers have demonstrated that it is possible to develop ambient awareness, that is, knowledge of others, after browsing social media, but it is still unclear whether and to what extent Twitter users also experience ambient intimacy, i.e., emotional closeness to others stemming from merely following them on Twitter. This paper is the first to theoretically distinguish the concept of ambient intimacy from ambient awareness. The paper investigates the degree to which Twitter users experience ambient awareness and intimacy. Moreover, we also examine the role of interaction history and message characteristics in this process. The results showed that Twitter users had experienced ambient intimacy but to a lesser degree than ambient awareness; the majority felt close to only a limited number of people in their Twitter network. Visibility of tweets and one-sided interaction with the target person predicted ambient intimacy. In addition, users were more likely to experience ambient intimacy toward a person when his or her tweets were perceived as more intimate, entertaining, and informative.
Recurrent Neural Networks for fast and robust vibration-based ground classification on mobile robots
2016-05-01

This paper investigates Recurrent Neural Networks (RNNs), particularly Dynamic Cortex Memories (DCMs), an extension of Long Short Term Memories (LSTMs) for classification of 14 different ground types based on vibration data. Also a simple regularization technique called Sequence Boundary Dropout (SBD) is introduced, which effectively enlarges the training set and improves generalization. The neural networks perform in the time domain without any explicit feature computation, while previous state-of-the-art methods extract features mainly in the frequency domain. The presented approach does not require a time window, is causal, and works just-in-time, such that a classification can be done online at each new time step. Furthermore, we show that the neural networks outperform previous methods significantly in terms of classification accuracy. Finally, we demonstrate that the networks retrained with Random Activation Preservation (RAP) can classify very early - within a fraction of a second - but robustly at the same time in a continuous recognition scenario with varying classes.
The CRESST-III low-mass WIMP detector
2016-05-01

The next generation direct dark matter experiment CRESST-III has a high potential to significantly increase the sensitivity to low-mass WIMPs (mx ≲10 GeV/c2). We present the new CRESST detector module: it consists of a 24 g CaWO4 crystal operated as a phonon detector and a 20x20 mm^2 silicon-on-sapphire light detector. The phonon energy threshold is lowered to ~100 eV and a light detector resolution of typically 5 eV is achieved. A fully-scintillating inner detector housing is realised which efficiently rejects events from surface alpha decays. The CaWO4 sticks holding the target crystal are also operated as calorimeters to discriminate all possible artefacts related to the support structure. A projection for the sensitivity to spin-independent WIMP-nucleon scattering is given for the first phase of CRESSTIII which will start beginning of 2016.
Robot arm pose estimation by pixel-wise regression of joint angles
2016-05-01

To achieve accurate vision-based control with a robotic arm, a good hand-eye coordination is required. However, knowing the current configuration of the arm can be very difficult due to noisy readings from joint encoders or an inaccurate hand-eye calibration. We propose an approach for robot arm pose estimation that uses depth images of the arm as input to directly estimate angular joint positions. This is a frame-by-frame method which does not rely on good initialisation of the solution from the previous frames or knowledge from the joint encoders. For estimation, we employ a random regression forest which is trained on synthetically generated data. We compare different training objectives of the forest and also analyse the influence of prior segmentation of the arms on accuracy. We show that this approach improves previous work both in terms of computational complexity and accuracy. Despite being trained on synthetic data only, we demonstrate that the estimation also works on real depth images.
NLRP3A439V Mutation in a Large Family with Cryopyrin-associated Periodic Syndrome: Description of Ophthalmologic Symptoms in Correlation with Other Organ Symptoms
2016-05-01

Objective. Cryopyrin-associated periodic syndrome (CAPS) is a group of inherited autoinflammatory disorders caused by mutations in the NLRP3 gene resulting in the overproduction of interleukin 1β. NLRP3 mutations cause a broad clinical phenotype of CAPS. The aims of the study were to evaluate clinical, laboratory, and genetic features of a 5-generation family with CAPS focusing in detail on ocular symptoms. Methods. In a retrospective observational cohort study, consecutive family members were screened for the presence of the NLRP3 mutation. Patients underwent standardized clinical, laboratory, and ophthalmological assessments. The genotype-specific risk of ophthalmological findings and other organ symptoms was determined. Results. Twenty-nine patients were clinically affected. The A439V mutation encoded by exon 3 of the NLRP3 gene was found in 15 of 37 family members (41%). The most common clinical features were musculoskeletal symptoms, headaches, and ophthalmological symptoms. The mutation-positive patients were characterized by more frequent skin rashes, ocular symptoms, arthralgia, arthritis, and severe Muckle-Wells syndrome (MWS) Disease Activity Score. Rosacea was diagnosed in 8 patients. Conclusion. The NLRP3 mutation A439V is associated with a heterogeneous clinical spectrum of familial cold autoinflammatory syndrome/MWS-overlap syndrome. Skin rash and eye diseases, such as conjunctivitis and uveitis, were positively correlated with this mutation.
RFID-enabled location fingerprinting based on similarity models from probabilistic similarity measures
2016-05-01

In this work we present a novel fingerprint similarity sensor model for the purpose of localizing a mobile robot with passive ultra-high frequency (UHF) radio-frequency identification (RFID) through location fingerprinting. We firstly evaluate the performance of probabilistic similarity measures applied to received signal strength (RSS) and compare them with previous results obtained with well known vector similarity measures. We furthermore extend the observation model used in a particle filter to dynamically adapt to the uncertainty of single candidate fingerprints by using their similarity to the current observation. For this purpose, we derive a new likelihood function and introduce an alternative way of selecting candidate fingerprints using a combination of their signal space similarity as well as the distance between the currently estimated pose and reference fingerprints. Results obtained from experiments in two different environments highlight the improved accuracy as well as robustness of the proposed methods.
The Sterically Demanding Thiosilyl Group SSi(SiMe3)3 as a Ligand in Transition Metal Chemistry
2016-05-01

Abstract The increasing number of metalloid clusters, synthesized in the last couple of years, gives new insights into the formation process of metals or semi‐metals. Metalloid clusters of the transition metals, especially the coinage metals are thereby of particular interest and the number of structurally characterized metalloid gold clusters has increased over the last decade. Most of these clusters are stabilized via aryl thiolate ligands. Herein, the synthesis and crystal structures of the lithium and potassium salts of the bulky SSi(SiMe 3 ) 3 ligand are presented together with the synthesis of suitable M I precursors ( M = Cu, Ag, Au) for further build‐up reactions to metalloid clusters.
The Archetype Tungsten Iodide Cluster Compound W3I8
2016-05-01

Abstract The tungsten iodide W 3 I 8 is obtained by thermal conversion of W 3 I 12 . The crystal structure of W 3 I 8 was solved and refined by means of powder X‐ray diffraction techniques. The structure is based on a nearly trigonal tungsten cluster core, with six edge‐capping iodido ligands and three apical iodido ligands, of which two are shared between clusters to generate chains. Cluster chains in the structure are arranged following the pattern of a sinusoidal wave.
New results on low-mass dark matter from the CRESST-II experiment
2016-05-01

The CRESST-II experiment is searching for dark matter particles via their elastic scattering off nuclei in a target material. The CRESST target consists of scintillating CaWO4 crystals which are operated as cryogenic calorimeters at millikelvin temperatures and read out by transition edge sensors. Each interaction in the CaWO4 target crystal produces a phonon signal and also a light signal that is measured by a secondary cryogenic calorimeter. The low energy thresholds of these detectors, combined with the presence of light nuclei in the target material, allow to probe the low-mass region of the parameter space for spin-independent dark matter-nucleon scattering with high sensitivity. In this contribution results from a blind analysis of one detector module operated in the latest measurement campaign are presented. An unprecedented sensitivity for the light dark matter has been obtained with 52kg live days and a threshold of 307eV for nuclear recoils, extending the reach of direct dark matter searches to the sub-GeV/c2 region.
Vps4A-mediated tumor suppression upon exosome modulation?
2016-05-01

In cancer, communication between tumor cells and components of its surrounding microenvironment is critical for tumor growth, progression and metastatic potential (1). Components of the tumor microenvironment include extracellular matrix structures, fibroblasts (myofibroblasts), immune-reactive and inflammatory cells, and endothelial cells. Importantly, therapeutic opportunities may be opened up by combined targeting of tumor cells and their microenvironment (2). In this regard, better understanding of the cellular mechanisms mediating the communication between tumor cells and their microenvironment is urgently required.
SOX: search for short baseline neutrino oscillations with Borexino
2016-05-01

The Borexino detector has convincingly shown its outstanding performances in the low energy regime through its accomplishments in the observation and study of the solar and geo neutrinos. It is then an ideal tool to perform a state of the art source-based experiment for testing the longstanding hypothesis of a fourth sterile neutrino with ∼ eV 2 mass, as suggested by several anomalies accumulated over the past three decades in source, reactor, and accelerator-based experiments. The SOX project aims at successively deploying two intense radioactive sources, made of Cerium (antineutrino) and Chromium (neutrino), respectively, in a dedicated pit located beneath the detector. The existence of such an ∼ eV 2 sterile neutrino would then show up as an unambiguous spatial and energy distortion in the count rate of neutrinos interacting within the active detector volume. This article reports on the latest developments about the first phase of the SOX experiment, namely CeSOX, and gives a realistic projection of CeSOX sensitivity to light sterile neutrinos in a simple (3+1) model.