KERT: Automatic Extraction and Ranking of Topical Keyphrases from Content-Representative Document Titles

We introduce KERT (Keyphrase Extraction and Ranking by Topic), a framework for topical keyphrase generation and ranking. By shifting from the unigram-centric traditional methods of unsupervised keyphrase extraction to a phrase-centric approach, we are able to directly compare and rank phrases of different lengths. We construct a topical keyphrase ranking function which implements the four criteria that represent high quality topical keyphrases (coverage, purity, phraseness, and completeness). The effectiveness of our approach is demonstrated on two collections of content-representative titles in the domains of Computer Science and Physics.Comment: 9 page

Hysteretic magnetoresistance in polymeric diodes

We report on hysteretic organic magnetoresistance (OMAR) in polymeric diodes. We found that magnitude and lineshape of OMAR depends strongly on the scan speed of the magnetic field and on the time delay between two successive measurements. The time-dependent OMAR phenomenon is universal for diodes made with various polymers. However, the width and magnitude of OMAR varied with the polymeric material. The suggestive reason for this hysteretic behavior are trapped carriers, which in presence of a magnetic field changes the ferromagnetic ground-state of the polymer leading to long spin relaxation time. These experimental observations are significant for clarification of the OMAR phenomenon

Quantifying the effects of harvesting on carbon fluxes and stocks in northern temperate forests

Harvest disturbance has substantial impacts on forest carbon (C) fluxes and stocks. The quantification of these effects is essential for the better understanding of forest C dynamics and informing forest management in the context of global change. We used a process-based forest ecosystem model, PnET-CN, to evaluate how, and by what mechanisms, clear-cuts alter ecosystem C fluxes, aboveground C stocks (AGC), and leaf area index (LAI) in northern temperate forests. We compared C fluxes and stocks predicted by the model and observed at two chronosequences of eddy covariance flux sites for deciduous broadleaf forests (DBF) and evergreen needleleaf forests (ENF) in the Upper Midwest region of northern Wisconsin and Michigan, USA. The average normalized root mean square error (NRMSE) and the Willmott index of agreement (d) for carbon fluxes, LAI, and AGC in the two chronosequences were 20% and 0.90, respectively. Simulated gross primary productivity (GPP) increased with stand age, reaching a maximum (1200–1500 g C m−2 yr−1) at 11–30 years of age, and leveled off thereafter (900–1000 g C m−2 yr−1). Simulated ecosystem respiration (ER) for both plant functional types (PFTs) was initially as high as 700–1000 g C m−2 yr−1 in the first or second year after harvesting, decreased with age (400–800 g C m−2 yr−1) before canopy closure at 10–25 years of age, and increased to 800–900 g C m−2 yr−1 with stand development after canopy recovery. Simulated net ecosystem productivity (NEP) for both PFTs was initially negative, with net C losses of 400–700 g C m−2 yr−1 for 6–17 years after clear-cuts, reaching peak values of 400–600 g C m−2 yr−1 at 14–29 years of age, and eventually stabilizing in mature forests (\u3e 60 years old), with a weak C sink (100–200 g C m−2 yr−1). The decline of NEP with age was caused by the relative flattening of GPP and gradual increase of ER. ENF recovered more slowly from a net C source to a net sink, and lost more C than DBF. This suggests that in general ENF may be slower to recover to full C assimilation capacity after stand-replacing harvests, arising from the slower development of photosynthesis with stand age. Our model results indicated that increased harvesting intensity would delay the recovery of NEP after clear-cuts, but this had little effect on C dynamics during late succession. Future modeling studies of disturbance effects will benefit from the incorporation of forest population dynamics (e.g., regeneration and mortality) and relationships between age-related model parameters and state variables (e.g., LAI) into the model

ROBO-CALLING PREVENTION WITH SOFTWARE-DEFINED NETWORKING IN A WIDE AREA NETWORK POLICY FOR UNIFIED COMMUNICATION

Techniques are described herein for blocking robo-calls, spam calls, and telemarketing calls, which are becoming an industry menace. Such calls are blocked by tightly integrating a Software-Defined Networking in a Wide Area Network (SDWAN) controller with a Do Not Call registry. Analytics are used to analyze traffic call patterns, security insights are leveraged such as known malicious Internet Protocol (IP) and domain addresses, and a Call Barring feature may also be applied. This information may be pushed to edge devices to ensure robo-calls do not terminate on SDWAN-led voice endpoints

What determines the fraction of elliptical galaxies in clusters?

We study the correlation between the morphological mix of cluster galaxies and the assembly history of the parent cluster by taking advantage of two independently developed semi-analytic models for galaxy formation and evolution. In our models, both the number of cluster members and that of elliptical members increase as a function of cluster mass, in such a way that the resulting elliptical fractions are approximately independent of cluster mass. The population of cluster ellipticals exhibit a marked bimodal distribution as a function of galaxy stellar mass, with a dip at masses $\sim 10^{10}\,{\rm M}_{\odot}$. In the framework of our models, this bimodality originates from the combination of a strongly decreasing number of galaxies with increasing stellar mass, and a correspondingly increasing probability of experiencing major mergers. We show that the correlation between the measured elliptical fraction and the assembly history of the parent cluster is weak, and that it becomes stronger in models that adopt longer galaxy merger times. We argue that this results from the combined effect of a decreasing bulge production due to a reduced number of mergers, and an increasing survival probability of pre-existing ellipticals, with the latter process being more important than the former.Comment: 8 pages, 3 figures, accepted for publication in MNRA

Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback

Ideally, we would place a robot in a real-world environment and leave it there improving on its own by gathering more experience autonomously. However, algorithms for autonomous robotic learning have been challenging to realize in the real world. While this has often been attributed to the challenge of sample complexity, even sample-efficient techniques are hampered by two major challenges - the difficulty of providing well "shaped" rewards, and the difficulty of continual reset-free training. In this work, we describe a system for real-world reinforcement learning that enables agents to show continual improvement by training directly in the real world without requiring painstaking effort to hand-design reward functions or reset mechanisms. Our system leverages occasional non-expert human-in-the-loop feedback from remote users to learn informative distance functions to guide exploration while leveraging a simple self-supervised learning algorithm for goal-directed policy learning. We show that in the absence of resets, it is particularly important to account for the current "reachability" of the exploration policy when deciding which regions of the space to explore. Based on this insight, we instantiate a practical learning system - GEAR, which enables robots to simply be placed in real-world environments and left to train autonomously without interruption. The system streams robot experience to a web interface only requiring occasional asynchronous feedback from remote, crowdsourced, non-expert humans in the form of binary comparative feedback. We evaluate this system on a suite of robotic tasks in simulation and demonstrate its effectiveness at learning behaviors both in simulation and the real world. Project website https://guided-exploration-autonomous-rl.github.io/GEAR/.Comment: Project website https://guided-exploration-autonomous-rl.github.io/GEAR

Polymer-based electrospray chips for mass spectrometry

In this paper, we present our development of a MEMS chip with an overhanging polymer microcapillary 2.5 mm in length and with a 5 µm x 10 µm orifice size at the tip. The fabricated chips have been successfully interfaced with a mass spectrometer (MS) to validate electrospray ionization (ESI) for biochemical analysis. The prediction of a reduction in Taylor cone size has also been observed with real time ESI fluid visualization from our chip. Built-in micro particle filters and centimeter long serpentine microchannels were fabricated on the chip with a low temperature process by using the Parylene polymer as a structural material, aluminum and photoresist as sacrificial layers, and bromine trifluoride (BrF_3) gas phase etching for final microcapillary releasing. The use of an overhanging polymer structure adds a new a level of mechanical robustness that was never achievable with other thin films. Functionality of our device was proven by consistent detection of myoglobin in a 200 nM solution at a flow rate of 35 nL/min and a voltage potential of 1.5 kV. This MS interface chip represents vital and significant improvements in MEMS process technology and MS functionality with respect to the silicon nitride (Si_xN_y) ESI nozzles previously reported

Optimization of 3D ZnO brush-like nanorods for dye-sensitized solar cells

© 2018 The Royal Society of Chemistry This is an Open Access article, distributed under the terms of the Creative Commons Attribution Unported 3.0 license (CC BY 3.0), https://creativecommons.org/licenses/by/3.0/ which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly citedIn a dye-sensitized solar cell (DSSC) the amount of adsorbed dye on the photoanode surface is a key factor that must be maximized in order to obtain enhanced DSSC performance. In this study 3D ZnO nanostructures, named brush-like, are demonstrated as alternative photoanodes. In these structures, long ZnO nanorods are covered with a metal-organic precursor, known as a layered-hydroxide zinc salt (LHZS), which is subsequently converted to crystalline ZnO using two-step annealing. The LHZS is able to easily grow on any surface, such as the ZnO nanorod surface, without needing the assistance of a seed-layer. Brush-like structures synthesized using different citrate concentrations in the growth solutions and different annealing conditions are characterized and tested as DSSC photoanodes. The best-performing structure reported in this study was obtained using the highest citrate concentration (1.808 mM) and the lowest temperature annealing condition in an oxidative environment. Conversion efficiency as high as 1.95% was obtained when these brush-like structures were employed as DSSC photoanodes. These results are extremely promising for the implementation of these innovative structures in enhanced DSSCs, as well as in other applications that require the maximization of surface area exposed by ZnO or similar semiconductors, such as gas- or bio-sensing or photocatalysis.Peer reviewedFinal Published versio

Carbon Flux Phenology from the Sky: Evaluation for Maize and Soybean

Carbon flux phenology is widely used to understand carbon flux dynamics and surface exchange processes. Vegetation phenology has been widely evaluated by remote sensors; however, very few studies have evaluated the use of vegetation phenology for identifying carbon flux phenology. Currently available techniques to derive net ecosystem exchange (NEE) from a satellite image use a single generic modeling subgroup for agricultural crops. But, carbon flux phenological processes vary highly with crop types and land management practices; this paper reexamines this assumption. Presented here are an evaluation of ground-truth remotely sensed vegetation indices with in situ NEE measurements and an identification of vegetation indices for estimating carbon flux phenology metrics by crop type. Results show that the performance of different vegetation indices as an indicator of phenology varies with crop type, particularly when identifying the start of a season and the peak of a season. Maize fields require vegetation indices that make use of the near-infrared and red reflectance bands, while soybean fields require those making use of the shortwave infrared (IR) and near-IR bands. In summary, the study identifies how to best utilize remote sensing technology as a crop-specific measurement tool