Showing papers by "Georgia Institute of Technology published in 2016"
TL;DR: This is the first direct detection of gravitational waves and the first observation of a binary black hole merger, and these observations demonstrate the existence of binary stellar-mass black hole systems.
Abstract: On September 14, 2015 at 09:50:45 UTC the two detectors of the Laser Interferometer Gravitational-Wave Observatory simultaneously observed a transient gravitational-wave signal. The signal sweeps upwards in frequency from 35 to 250 Hz with a peak gravitational-wave strain of $1.0 \times 10^{-21}$. It matches the waveform predicted by general relativity for the inspiral and merger of a pair of black holes and the ringdown of the resulting single black hole. The signal was observed with a matched-filter signal-to-noise ratio of 24 and a false alarm rate estimated to be less than 1 event per 203 000 years, equivalent to a significance greater than 5.1 {\sigma}. The source lies at a luminosity distance of $410^{+160}_{-180}$ Mpc corresponding to a redshift $z = 0.09^{+0.03}_{-0.04}$. In the source frame, the initial black hole masses are $36^{+5}_{-4} M_\odot$ and $29^{+4}_{-4} M_\odot$, and the final black hole mass is $62^{+4}_{-4} M_\odot$, with $3.0^{+0.5}_{-0.5} M_\odot c^2$ radiated in gravitational waves. All uncertainties define 90% credible intervals.These observations demonstrate the existence of binary stellar-mass black hole systems. This is the first direct detection of gravitational waves and the first observation of a binary black hole merger.
9,596 citations
TL;DR: The new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies less on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence.
Abstract: Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.
3,902 citations
TL;DR: This second gravitational-wave observation provides improved constraints on stellar populations and on deviations from general relativity.
Abstract: We report the observation of a gravitational-wave signal produced by the coalescence of two stellar-mass black holes. The signal, GW151226, was observed by the twin detectors of the Laser Interferometer Gravitational-Wave Observatory (LIGO) on December 26, 2015 at 03:38:53 UTC. The signal was initially identified within 70 s by an online matched-filter search targeting binary coalescences. Subsequent off-line analyses recovered GW151226 with a network signal-to-noise ratio of 13 and a significance greater than 5 σ. The signal persisted in the LIGO frequency band for approximately 1 s, increasing in frequency and amplitude over about 55 cycles from 35 to 450 Hz, and reached a peak gravitational strain of 3.4+0.7−0.9×10−22. The inferred source-frame initial black hole masses are 14.2+8.3−3.7M⊙ and 7.5+2.3−2.3M⊙ and the final black hole mass is 20.8+6.1−1.7M⊙. We find that at least one of the component black holes has spin greater than 0.2. This source is located at a luminosity distance of 440+180−190 Mpc corresponding to a redshift 0.09+0.03−0.04. All uncertainties define a 90 % credible interval. This second gravitational-wave observation provides improved constraints on stellar populations and on deviations from general relativity.
3,448 citations
TL;DR: This list is not exhaustive; almost all commercial chemicals arise from a separation process that could be improved, and here, seven chemical separation processes that, if improved, would reap great global benefits.
Abstract: Purifying mixtures without using heat would lower global energy use, emissions and pollution — and open up new routes to resources, say David S. Sholl and Ryan P. Lively.
2,281 citations
TL;DR: In this article, a plasmon-enhanced solar desalination device, fabricated by the self-assembly of aluminium nanoparticles into a three-dimensional porous membrane, is demonstrated.
Abstract: Self-assembling aluminium nanoparticles are used to make a plasmon-enhanced device for desalination. Plasmonics has generated tremendous excitement because of its unique capability to focus light into subwavelength volumes1, beneficial for various applications such as light harvesting2,3, photodetection4, sensing5, catalysis6 and so on. Here we demonstrate a plasmon-enhanced solar desalination device, fabricated by the self–assembly of aluminium nanoparticles into a three-dimensional porous membrane. The formed porous plasmonic absorber can float naturally on water surface, efficiently absorb a broad solar spectrum (>96%) and focus the absorbed energy at the surface of the water to enable efficient (∼90%) and effective desalination (a decrease of four orders of magnitude). The durability of the devices has also been examined, indicating a stable performance over 25 cycles under various illumination conditions. The combination of the significant desalination effect, the abundance and low cost of the materials, and the scalable production processes suggest that this type of plasmon-enhanced solar desalination device could provide a portable desalination solution.
1,567 citations
TL;DR: It is found that the final remnant's mass and spin, as determined from the low-frequency and high-frequency phases of the signal, are mutually consistent with the binary black-hole solution in general relativity.
Abstract: The LIGO detection of GW150914 provides an unprecedented opportunity to study the two-body motion of a compact-object binary in the large-velocity, highly nonlinear regime, and to witness the final merger of the binary and the excitation of uniquely relativistic modes of the gravitational field. We carry out several investigations to determine whether GW150914 is consistent with a binary black-hole merger in general relativity. We find that the final remnant’s mass and spin, as determined from the low-frequency (inspiral) and high-frequency (postinspiral) phases of the signal, are mutually consistent with the binary black-hole solution in general relativity. Furthermore, the data following the peak of GW150914 are consistent with the least-damped quasinormal mode inferred from the mass and spin of the remnant black hole. By using waveform models that allow for parametrized general-relativity violations during the inspiral and merger phases, we perform quantitative tests on the gravitational-wave phase in the dynamical regime and we determine the first empirical bounds on several high-order post-Newtonian coefficients. We constrain the graviton Compton wavelength, assuming that gravitons are dispersed in vacuum in the same way as particles with mass, obtaining a 90%-confidence lower bound of 1013 km. In conclusion, within our statistical uncertainties, we find no evidence for violations of general relativity in the genuinely strong-field regime of gravity.
1,421 citations
TL;DR: Progress in nanogenerators for mechanical energy harvesting is reviewed, mainly including two key technologies: flexible piezoelectric nanognerators (PENGs) and flexible triboelectrics nanogsenerators (TENGs).
Abstract: Flexible nanogenerators that efficiently convert mechanical energy into electrical energy have been extensively studied because of their great potential for driving low-power personal electronics and self-powered sensors. Integration of flexibility and stretchability to nanogenerator has important research significance that enables applications in flexible/stretchable electronics, organic optoelectronics, and wearable electronics. Progress in nanogenerators for mechanical energy harvesting is reviewed, mainly including two key technologies: flexible piezoelectric nanogenerators (PENGs) and flexible triboelectric nanogenerators (TENGs). By means of material classification, various approaches of PENGs based on ZnO nanowires, lead zirconate titanate (PZT), poly(vinylidene fluoride) (PVDF), 2D materials, and composite materials are introduced. For flexible TENG, its structural designs and factors determining its output performance are discussed, as well as its integration, fabrication and applications. The latest representative achievements regarding the hybrid nanogenerator are also summarized. Finally, some perspectives and challenges in this field are discussed.
1,325 citations
TL;DR: It is concluded that there are many new materials that could play a role in emerging DAC technologies, however, these materials need to be further investigated and developed with a practical sorbent-air contacting process in mind if society is to make rapid progress in deploying DAC as a means of mitigating climate change.
Abstract: The increase in the global atmospheric CO2 concentration resulting from over a century of combustion of fossil fuels has been associated with significant global climate change. With the global population increase driving continued increases in fossil fuel use, humanity’s primary reliance on fossil energy for the next several decades is assured. Traditional modes of carbon capture such as precombustion and postcombustion CO2 capture from large point sources can help slow the rate of increase of the atmospheric CO2 concentration, but only the direct removal of CO2 from the air, or “direct air capture” (DAC), can actually reduce the global atmospheric CO2 concentration. The past decade has seen a steep rise in the use of chemical sorbents that are cycled through sorption and desorption cycles for CO2 removal from ultradilute gases such as air. This Review provides a historical overview of the field of DAC, along with an exhaustive description of the use of chemical sorbents targeted at this application. Solv...
1,217 citations
TL;DR: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers as discussed by the authors.
Abstract: The first observational run of the Advanced LIGO detectors, from September 12, 2015 to January 19, 2016, saw the first detections of gravitational waves from binary black hole mergers. In this paper we present full results from a search for binary black hole merger signals with total masses up to 100M⊙ and detailed implications from our observations of these systems. Our search, based on general-relativistic models of gravitational wave signals from binary black hole systems, unambiguously identified two signals, GW150914 and GW151226, with a significance of greater than 5σ over the observing period. It also identified a third possible signal, LVT151012, with substantially lower significance, which has a 87% probability of being of astrophysical origin. We provide detailed estimates of the parameters of the observed systems. Both GW150914 and GW151226 provide an unprecedented opportunity to study the two-body motion of a compact-object binary in the large velocity, highly nonlinear regime. We do not observe any deviations from general relativity, and place improved empirical bounds on several high-order post-Newtonian coefficients. From our observations we infer stellar-mass binary black hole merger rates lying in the range 9−240Gpc−3yr−1. These observations are beginning to inform astrophysical predictions of binary black hole formation rates, and indicate that future observing runs of the Advanced detector network will yield many more gravitational wave detections.
1,172 citations
TL;DR: The effects of nanoparticle size on cellular interaction and in vivo pharmacokinetics, including cellular uptake, biodistribution and circulation half-life of nanoparticles are reviewed.
1,069 citations
University of British Columbia1, National Autonomous University of Mexico2, Arizona State University3, National University of Cordoba4, University of Oxford5, University of Vermont6, Helmholtz Centre for Environmental Research - UFZ7, Charles Sturt University8, Lüneburg University9, Oregon State University10, Georgia Institute of Technology11, University of Kiel12, Ikerbasque13, University of Victoria14
TL;DR: It is proposed that focusing only on instrumental or intrinsic values may fail to resonate with views on personal and collective well-being, or “what is right,” with regard to nature and the environment, and it is time to engage seriously with a third class of values, one with diverse roots and current expressions: relational values.
Abstract: A cornerstone of environmental policy is the debate over protecting nature for humans’ sake (instrumental values) or for nature’s (intrinsic values) (1). We propose that focusing only on instrumental or intrinsic values may fail to resonate with views on personal and collective well-being, or “what is right,” with regard to nature and the environment. Without complementary attention to other ways that value is expressed and realized by people, such a focus may inadvertently promote worldviews at odds with fair and desirable futures. It is time to engage seriously with a third class of values, one with diverse roots and current expressions: relational values. By doing so, we reframe the discussion about environmental protection, and open the door to new, potentially more productive policy approaches.
Posted Content•
TL;DR: This article proposed an adaptive attention model with a visual sentinel to decide whether to attend to the image and where, in order to extract meaningful information for sequential word generation, which set the new state-of-the-art by a significant margin.
Abstract: Attention-based neural encoder-decoder frameworks have been widely adopted for image captioning. Most methods force visual attention to be active for every generated word. However, the decoder likely requires little to no visual information from the image to predict non-visual words such as "the" and "of". Other words that may seem visual can often be predicted reliably just from the language model e.g., "sign" after "behind a red stop" or "phone" following "talking on a cell". In this paper, we propose a novel adaptive attention model with a visual sentinel. At each time step, our model decides whether to attend to the image (and if so, to which regions) or to the visual sentinel. The model decides whether to attend to the image and where, in order to extract meaningful information for sequential word generation. We test our method on the COCO image captioning 2015 challenge dataset and Flickr30K. Our approach sets the new state-of-the-art by a significant margin.
TL;DR: An efficient fused-ring electron acceptor based on indacenodithieno[3,2-b]thiophene core and thienyl side-chains for organic solar cells (OSCs) is developed and rivals some of the highest efficiencies for single junction OSCs based on fullerene acceptors.
Abstract: We develop an efficient fused-ring electron acceptor (ITIC-Th) based on indacenodithieno[3,2-b]thiophene core and thienyl side-chains for organic solar cells (OSCs). Relative to its counterpart with phenyl side-chains (ITIC), ITIC-Th shows lower energy levels (ITIC-Th: HOMO = −5.66 eV, LUMO = −3.93 eV; ITIC: HOMO = −5.48 eV, LUMO = −3.83 eV) due to the σ-inductive effect of thienyl side-chains, which can match with high-performance narrow-band-gap polymer donors and wide-band-gap polymer donors. ITIC-Th has higher electron mobility (6.1 × 10–4 cm2 V–1 s–1) than ITIC (2.6 × 10–4 cm2 V–1 s–1) due to enhanced intermolecular interaction induced by sulfur–sulfur interaction. We fabricate OSCs by blending ITIC-Th acceptor with two different low-band-gap and wide-band-gap polymer donors. In one case, a power conversion efficiency of 9.6% was observed, which rivals some of the highest efficiencies for single junction OSCs based on fullerene acceptors.
TL;DR: The data around the time of the event were analyzed coherently across the LIGO network using a suite of accurate waveform models that describe gravitational waves from a compact binary system in general relativity.
Abstract: On September 14, 2015, the Laser Interferometer Gravitational-wave Observatory (LIGO) detected a gravitational-wave transient (GW150914); we characterise the properties of the source and its parameters. The data around the time of the event were analysed coherently across the LIGO network using a suite of accurate waveform models that describe gravitational waves from a compact binary system in general relativity. GW150914 was produced by a nearly equal mass binary black hole of $36^{+5}_{-4} M_\odot$ and $29^{+4}_{-4} M_\odot$ (for each parameter we report the median value and the range of the 90% credible interval). The dimensionless spin magnitude of the more massive black hole is bound to be $0.7$ (at 90% probability). The luminosity distance to the source is $410^{+160}_{-180}$ Mpc, corresponding to a redshift $0.09^{+0.03}_{-0.04}$ assuming standard cosmology. The source location is constrained to an annulus section of $590$ deg$^2$, primarily in the southern hemisphere. The binary merges into a black hole of $62^{+4}_{-4} M_\odot$ and spin $0.67^{+0.05}_{-0.07}$. This black hole is significantly more massive than any other known in the stellar-mass regime.
National Oceanic and Atmospheric Administration1, University of Colorado Boulder2, Cornell University3, Georgia Institute of Technology4, National Center for Atmospheric Research5, Scripps Institution of Oceanography6, Hokkaido University7, University of Tokyo8, University of Hawaii at Manoa9, University of Wisconsin-Madison10
TL;DR: In this article, the Pacific decadal oscillation (PDO) is not a single phenomenon, but is instead the result of a combination of different physical processes, including remote tropical forcing and local North Pacific atmosphere-ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns.
Abstract: The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within the meteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of ...
27 Mar 2016
TL;DR: The enveomics collection, a growing set of actively maintained scripts for several recurrent and specialized tasks in microbial genomics and metagenomics, is described and a graphical user interface and several case studies are presented.
Abstract: Genomic and metagenomic analyses are increasingly becoming commonplace in several areas of biological research, but recurrent specialized analyses are frequently reported as in-house scripts rarely available after publication. We describe the enveomics collection, a growing set of actively maintained scripts for several recurrent and specialized tasks in microbial genomics and metagenomics, and present a graphical user interface and several case studies. Our resource includes previously described as well as new algorithms such as Transformed-space Resampling In Biased Sets (TRIBS), a novel method to evaluate phylogenetic underor over-dispersion in reference sets with strong phylogenetic bias. The enveomics collection is freely available under the terms of the Artistic License 2.0 at https://github.com/lmrodriguezr/enveomics and for online analysis at http://enve-omics.ce.gatech.edu .
TL;DR: The authors deployed the reconfigurable fabric in a bed of 1,632 servers and FPGAs in a production datacenter and successfully used it to accelerate the ranking portion of the Bing Web search engine by nearly a factor of two.
Abstract: Datacenter workloads demand high computational capabilities, flexibility, power efficiency, and low cost It is challenging to improve all of these factors simultaneously To advance datacenter capabilities beyond what commodity server designs can provide, we designed and built a composable, reconfigurable hardware fabric based on field programmable gate arrays (FPGA) Each server in the fabric contains one FPGA, and all FPGAs within a 48-server rack are interconnected over a low-latency, high-bandwidth networkWe describe a medium-scale deployment of this fabric on a bed of 1632 servers, and measure its effectiveness in accelerating the ranking component of the Bing web search engine We describe the requirements and architecture of the system, detail the critical engineering challenges and solutions needed to make the system robust in the presence of failures, and measure the performance, power, and resilience of the system Under high load, the large-scale reconfigurable fabric improves the ranking throughput of each server by 95% at a desirable latency distribution or reduces tail latency by 29% at a fixed throughput In other words, the reconfigurable fabric enables the same throughput using only half the number of servers
TL;DR: Chen et al. as mentioned in this paper presented a micro-cable power textile for simultaneously harvesting energy from ambient sunshine and mechanical movement, which can continuously power an electronic watch, directly charge a cell phone and drive water splitting reactions.
Abstract: Developing lightweight, flexible, foldable and sustainable power sources with simple transport and storage remains a challenge and an urgent need for the advancement of next-generation wearable electronics. Here, we report a micro-cable power textile for simultaneously harvesting energy from ambient sunshine and mechanical movement. Solar cells fabricated from lightweight polymer fibres into micro cables are then woven via a shuttle-flying process with fibre-based triboelectric nanogenerators to create a smart fabric. A single layer of such fabric is 320 μm thick and can be integrated into various cloths, curtains, tents and so on. This hybrid power textile, fabricated with a size of 4 cm by 5 cm, was demonstrated to charge a 2 mF commercial capacitor up to 2 V in 1 min under ambient sunlight in the presence of mechanical excitation, such as human motion and wind blowing. The textile could continuously power an electronic watch, directly charge a cell phone and drive water splitting reactions. Energy harvesting from the environment by portable and flexible power sources can power a variety of devices sustainably. Chen et al. report a hybrid power textile with solar cells and triboelectric nanogenerators that can simultaneously harvest solar and mechanical energy.
TL;DR: Baker1 is presented, a pipeline for unsupervised RNA-Seq-based genome annotation that combines the advantages of GeneMark-ET and AUGUSTUS and was observed that BRAKER1 was more accurate than MAKER2 when it is using RNA- Seq as sole source for training and prediction.
Abstract: MOTIVATION Gene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction. RESULTS We present BRAKER1, a pipeline for unsupervised RNA-Seq-based genome annotation that combines the advantages of GeneMark-ET and AUGUSTUS. As input, BRAKER1 requires a genome assembly file and a file in bam-format with spliced alignments of RNA-Seq reads to the genome. First, GeneMark-ET performs iterative training and generates initial gene structures. Second, AUGUSTUS uses predicted genes for training and then integrates RNA-Seq read information into final gene predictions. In our experiments, we observed that BRAKER1 was more accurate than MAKER2 when it is using RNA-Seq as sole source for training and prediction. BRAKER1 does not require pre-trained parameters or a separate expert-prepared training step. AVAILABILITY AND IMPLEMENTATION BRAKER1 is available for download at http://bioinf.uni-greifswald.de/bioinf/braker/ and http://exon.gatech.edu/GeneMark/ CONTACT katharina.hoff@uni-greifswald.de or borodovsky@gatech.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
TL;DR: The discovery of the GW150914 with the Advanced LIGO detectors provides the first observational evidence for the existence of binary black-hole systems that inspiral and merge within the age of the Universe as mentioned in this paper.
Abstract: The discovery of the gravitational-wave source GW150914 with the Advanced LIGO detectors provides the first observational evidence for the existence of binary black-hole systems that inspiral and merge within the age of the Universe. Such black-hole mergers have been predicted in two main types of formation models, involving isolated binaries in galactic fields or dynamical interactions in young and old dense stellar environments. The measured masses robustly demonstrate that relatively "heavy" black holes (≳25M⊙) can form in nature. This discovery implies relatively weak massive-star winds and thus the formation of GW150914 in an environment with metallicity lower than ∼1/2 of the solar value. The rate of binary black-hole mergers inferred from the observation of GW150914 is consistent with the higher end of rate predictions (≳1Gpc−3yr−1) from both types of formation models. The low measured redshift (z∼0.1) of GW150914 and the low inferred metallicity of the stellar progenitor imply either binary black-hole formation in a low-mass galaxy in the local Universe and a prompt merger, or formation at high redshift with a time delay between formation and merger of several Gyr. This discovery motivates further studies of binary-black-hole formation astrophysics. It also has implications for future detections and studies by Advanced LIGO and Advanced Virgo, and gravitational-wave detectors in space.
TL;DR: There are highlights of four emerging areas in the field of drug delivery: systemic RNA delivery, drug delivery for localized therapy, oral drug delivery systems, and biologic drugDelivery systems, where the barriers to effective drug delivery as well as chemical and materials advances are presented.
Abstract: Medicine relies on the use of pharmacologically active agents (drugs) to manage and treat disease. However, drugs are not inherently effective; the benefit of a drug is directly related to the manner by which it is administered or delivered. Drug delivery can affect drug pharmacokinetics, absorption, distribution, metabolism, duration of therapeutic effect, excretion, and toxicity. As new therapeutics (e.g., biologics) are being developed, there is an accompanying need for improved chemistries and materials to deliver them to the target site in the body, at a therapeutic concentration, and for the required period of time. In this Perspective, we provide an historical overview of drug delivery and controlled release followed by highlights of four emerging areas in the field of drug delivery: systemic RNA delivery, drug delivery for localized therapy, oral drug delivery systems, and biologic drug delivery systems. In each case, we present the barriers to effective drug delivery as well as chemical and mater...
TL;DR: A novel and scalable self-charging power textile is realized by combining yarn supercapacitors and fabric triboelectric nanogenerators as energy-harvesting devices.
Abstract: A novel and scalable self-charging power textile is realized by combining yarn supercapacitors and fabric triboelectric nanogenerators as energy-harvesting devices.
TL;DR: A hybridized self-powered textile for simultaneously collecting solar energy and random body motion energy was demonstrated and can be easily woven into electronic textiles to fabricate smart clothes to sustainably operate mobile or wearable electronics.
Abstract: Wearable electronics fabricated on lightweight and flexible substrate are believed to have great potential for portable devices, but their applications are limited by the life span of their batteries We propose a hybridized self-charging power textile system with the aim of simultaneously collecting outdoor sunshine and random body motion energies and then storing them in an energy storage unit Both of the harvested energies can be easily converted into electricity by using fiber-shaped dye-sensitized solar cells (for solar energy) and fiber-shaped triboelectric nanogenerators (for random body motion energy) and then further stored as chemical energy in fiber-shaped supercapacitors Because of the all–fiber-shaped structure of the entire system, our proposed hybridized self-charging textile system can be easily woven into electronic textiles to fabricate smart clothes to sustainably operate mobile or wearable electronics
TL;DR: In this paper, a high-resolution projection microstereolithography (PμSL) approach is used to create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures.
Abstract: We present a new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures. The approach is based on high resolution projection microstereolithography (PμSL) and uses a family of photo-curable methacrylate based copolymer networks. We designed the constituents and compositions to exhibit desired thermomechanical behavior (including rubbery modulus, glass transition temperature and failure strain which is more than 300% and larger than any existing printable materials) to enable controlled shape memory behavior. We used a high resolution, high contrast digital micro display to ensure high resolution of photo-curing methacrylate based SMPs that requires higher exposure energy than more common acrylate based polymers. An automated material exchange process enables the manufacture of 3D composite architectures from multiple photo-curable SMPs. In order to understand the behavior of the 3D composite microarchitectures, we carry out high fidelity computational simulations of their complex nonlinear, time-dependent behavior and study important design considerations including local deformation, shape fixity and free recovery rate. Simulations are in good agreement with experiments for a series of single and multimaterial components and can be used to facilitate the design of SMP 3D structures.
01 Jun 2016
TL;DR: In this article, a two-branch neural network with multiple layers of linear projections followed by nonlinearities is trained using a largemargin objective that combines cross-view ranking constraints with within-view neighborhood structure preservation constraints inspired by metric learning.
Abstract: This paper proposes a method for learning joint embeddings of images and text using a two-branch neural network with multiple layers of linear projections followed by nonlinearities. The network is trained using a largemargin objective that combines cross-view ranking constraints with within-view neighborhood structure preservation constraints inspired by metric learning literature. Extensive experiments show that our approach gains significant improvements in accuracy for image-to-text and textto-image retrieval. Our method achieves new state-of-theart results on the Flickr30K and MSCOCO image-sentence datasets and shows promise on the new task of phrase localization on the Flickr30K Entities dataset.
13 Aug 2016
TL;DR: The Recurrent Marked Temporal Point Process is proposed to simultaneously model the event timings and the markers, and uses a recurrent neural network to automatically learn a representation of influences from the event history, and an efficient stochastic gradient algorithm is developed for learning the model parameters.
Abstract: Large volumes of event data are becoming increasingly available in a wide variety of applications, such as healthcare analytics, smart cities and social network analysis. The precise time interval or the exact distance between two events carries a great deal of information about the dynamics of the underlying systems. These characteristics make such data fundamentally different from independently and identically distributed data and time-series data where time and space are treated as indexes rather than random variables. Marked temporal point processes are the mathematical framework for modeling event data with covariates. However, typical point process models often make strong assumptions about the generative processes of the event data, which may or may not reflect the reality, and the specifically fixed parametric assumptions also have restricted the expressive power of the respective processes. Can we obtain a more expressive model of marked temporal point processes? How can we learn such a model from massive data? In this paper, we propose the Recurrent Marked Temporal Point Process (RMTPP) to simultaneously model the event timings and the markers. The key idea of our approach is to view the intensity function of a temporal point process as a nonlinear function of the history, and use a recurrent neural network to automatically learn a representation of influences from the event history. We develop an efficient stochastic gradient algorithm for learning the model parameters which can readily scale up to millions of events. Using both synthetic and real world datasets, we show that, in the case where the true models have parametric specifications, RMTPP can learn the dynamics of such models without the need to know the actual parametric forms; and in the case where the true models are unknown, RMTPP can also learn the dynamics and achieve better predictive performance than other parametric alternatives based on particular prior assumptions.
TL;DR: In this article, a simple and effective strategy for enhancing ORR and OER electrocatalytic activity in alkaline solution by introducing A-site cation deficiency in LaFeO3 perovskite was reported.
Abstract: Development of cost-effective and efficient electrocatalysts for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is of prime importance to emerging renewable energy technologies. Here, we report a simple and effective strategy for enhancing ORR and OER electrocatalytic activity in alkaline solution by introducing A-site cation deficiency in LaFeO3 perovskite; the enhancement effect is more pronounced for the OER than the ORR. Among the A-site cation deficient perovskites studied, La0.95FeO3-δ (L0.95F) demonstrates the highest ORR and OER activity and, hence, the best bifunctionality. The dramatic enhancement is attributed to the creation of surface oxygen vacancies and a small amount of Fe4+ species. This work highlights the importance of tuning cation deficiency in perovskites as an effective strategy for enhancing ORR and OER activity for applications in various oxygen-based energy storage and conversion processes.
TL;DR: A stimuli-responsive clustered nanoparticle (iCluster) was developed and justified that its adaptive alterations of physicochemical properties in accordance with the endogenous stimuli of the tumor microenvironment made possible the ultimate overcoming of these barriers, especially the bottleneck of tumor penetration.
Abstract: A principal goal of cancer nanomedicine is to deliver therapeutics effectively to cancer cells within solid tumors. However, there are a series of biological barriers that impede nanomedicine from reaching target cells. Here, we report a stimuli-responsive clustered nanoparticle to systematically overcome these multiple barriers by sequentially responding to the endogenous attributes of the tumor microenvironment. The smart polymeric clustered nanoparticle (iCluster) has an initial size of ∼100 nm, which is favorable for long blood circulation and high propensity of extravasation through tumor vascular fenestrations. Once iCluster accumulates at tumor sites, the intrinsic tumor extracellular acidity would trigger the discharge of platinum prodrug-conjugated poly(amidoamine) dendrimers (diameter ∼5 nm). Such a structural alteration greatly facilitates tumor penetration and cell internalization of the therapeutics. The internalized dendrimer prodrugs are further reduced intracellularly to release cisplatin to kill cancer cells. The superior in vivo antitumor activities of iCluster are validated in varying intractable tumor models including poorly permeable pancreatic cancer, drug-resistant cancer, and metastatic cancer, demonstrating its versatility and broad applicability.
Proceedings Article•
01 Jan 2016
TL;DR: In this paper, a two-level neural attention model is proposed to detect influential past visits and significant clinical variables within those visits (e.g. key diagnoses) in reverse time order so that recent clinical visits are likely to receive higher attention.
Abstract: Accuracy and interpretability are two dominant features of successful predictive models. Typically, a choice must be made in favor of complex black box models such as recurrent neural networks (RNN) for accuracy versus less accurate but more interpretable traditional models such as logistic regression. This tradeoff poses challenges in medicine where both accuracy and interpretability are important. We addressed this challenge by developing the REverse Time AttentIoN model (RETAIN) for application to Electronic Health Records (EHR) data. RETAIN achieves high accuracy while remaining clinically interpretable and is based on a two-level neural attention model that detects influential past visits and significant clinical variables within those visits (e.g. key diagnoses). RETAIN mimics physician practice by attending the EHR data in a reverse time order so that recent clinical visits are likely to receive higher attention. RETAIN was tested on a large health system EHR dataset with 14 million visits completed by 263K patients over an 8 year period and demonstrated predictive accuracy and computational scalability comparable to state-of-the-art methods such as RNN, and ease of interpretability comparable to traditional models.
Journal Article•
TL;DR: A new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures based on high resolution projection microstereolithography (PμSL) and uses a family of photo-curable methacrylate based copolymer networks.
Abstract: We present a new 4D printing approach that can create high resolution (up to a few microns), multimaterial shape memory polymer (SMP) architectures The approach is based on high resolution projection microstereolithography (PμSL) and uses a family of photo-curable methacrylate based copolymer networks We designed the constituents and compositions to exhibit desired thermomechanical behavior (including rubbery modulus, glass transition temperature and failure strain which is more than 300% and larger than any existing printable materials) to enable controlled shape memory behavior We used a high resolution, high contrast digital micro display to ensure high resolution of photo-curing methacrylate based SMPs that requires higher exposure energy than more common acrylate based polymers An automated material exchange process enables the manufacture of 3D composite architectures from multiple photo-curable SMPs In order to understand the behavior of the 3D composite microarchitectures, we carry out high fidelity computational simulations of their complex nonlinear, time-dependent behavior and study important design considerations including local deformation, shape fixity and free recovery rate Simulations are in good agreement with experiments for a series of single and multimaterial components and can be used to facilitate the design of SMP 3D structures