Showing papers by "Bar-Ilan University published in 2017"
TL;DR: This article found that participants on both platforms were more naive and less dishonest compared to MTurk participants, and ProA and CrowdFlower participants produced data quality that was higher than CF's and comparable to M-Turk's.
1,537 citations
TL;DR: In this article, two-dimensional transition metal carbides exhibit high gravimetric, volumetric, and areal capacitance values at high charcoefficients at high temperature.
Abstract: Pseudocapacitors based on redox-active materials have relatively high energy density but suffer from low power capability. Here the authors report that two-dimensional transition metal carbides exhibit high gravimetric, volumetric and areal capacitance values at high char…
1,477 citations
TL;DR: In this article, the authors present the recent advances in the field of composite materials that include at least one carbon-based component for supercapacitor electrodes, focusing on cases in which a single material by itself suffers from a drawback that can be overcome by combining it with other components, enabling the fabrication of a composite material with enhanced performance.
Abstract: Electrochemical capacitors, so-called supercapacitors, play an important role in energy storage and conversion systems. In the last decade, with the increasing volume of scientific activity and publications in this field, researchers have developed better tools to improve electrode materials. Although carbonaceous materials seem the most suitable for supercapacitor applications, a large diversity of materials has been proposed and studied. Yet, in order to accomplish performance beyond the limitations of each material, mainly in terms of energy density and durability, composite materials have been implemented, most of them being the combinations of carbon-based materials and other components. In this review, we present the recent advances in the field of composite materials that include at least one carbon-based component for supercapacitor electrodes. We focus on cases in which a single material by itself suffers from a drawback that can be overcome by combining it with other components, enabling the fabrication of a composite material with enhanced performance. We present several important compositions as well as the major routes of synthesis, characterization and performance of composite materials in this field.
1,042 citations
Book•
17 Apr 2017TL;DR: Neural networks are a family of powerful machine learning models as mentioned in this paper, and they have been widely used in natural language processing applications such as machine translation, syntactic parsing, and multi-task learning.
Abstract: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
625 citations
Proceedings Article•
24 Apr 2017TL;DR: This study presents a neural-network approach that optimizes the same likelihood function as optimized by the EM algorithm but extended to the case where the noisy labels are dependent on the features in addition to the correct labels.
Abstract: The availability of large datsets has enabled neural networks to achieve impressive recognition results. However, the presence of inaccurate class labels is known to deteriorate the performance of even the best classifiers in a broad range of classification problems. Noisy labels also tend to be more harmful than noisy attributes. When the observed label is noisy, we can view the correct label as a latent random variable and model the noise processes by a communication channel with unknown parameters. Thus we can apply the EM algorithm to find the parameters of both the network and the noise and to estimate the correct label. In this study we present a neural-network approach that optimizes the same likelihood function as optimized by the EM algorithm. The noise is explicitly modeled by an additional softmax layer that connects the correct labels to the noisy ones. This scheme is then extended to the case where the noisy labels are dependent on the features in addition to the correct labels. Experimental results demonstrate that this approach outperforms previous methods.
592 citations
557 citations
TL;DR: This paper proposes to analyze a large number of established and recent techniques according to four transverse axes: 1) the acoustic impulse response model, 2) the spatial filter design criterion, 3) the parameter estimation algorithm, and 4) optional postfiltering.
Abstract: Speech enhancement and separation are core problems in audio signal processing, with commercial applications in devices as diverse as mobile phones, conference call systems, hands-free systems, or hearing aids. In addition, they are crucial preprocessing steps for noise-robust automatic speech and speaker recognition. Many devices now have two to eight microphones. The enhancement and separation capabilities offered by these multichannel interfaces are usually greater than those of single-channel interfaces. Research in speech enhancement and separation has followed two convergent paths, starting with microphone array processing and blind source separation, respectively. These communities are now strongly interrelated and routinely borrow ideas from each other. Yet, a comprehensive overview of the common foundations and the differences between these approaches is lacking at present. In this paper, we propose to fill this gap by analyzing a large number of established and recent techniques according to four transverse axes: 1 the acoustic impulse response model, 2 the spatial filter design criterion, 3 the parameter estimation algorithm, and 4 optional postfiltering. We conclude this overview paper by providing a list of software and data resources and by discussing perspectives and future trends in the field.
452 citations
TL;DR: A conceptual framework on human attachments is presented, integrating insights from animal research with neuroimaging studies, and may open perspectives on the 'situated' brain and initiate dialog between science and humanities, arts, and clinical wisdom.
432 citations
TL;DR: It is proposed that an emphasis on purely performance-based metrics has diluted the community’s understanding of why a certain methodology is (un)successful and the need for more consistent and fundamental research on the interfacial electrochemistry on Li metal anodes is motivated.
Abstract: Li metal anodes are often considered a “holy grail” in the field of rechargeable batteries. Accordingly, the research community continuously seeks new strategies to improve their cyclability and reduce interfacial degradation. However, many recent reports focus on approaches that mitigate the symptoms of poor performance due to dendrites without addressing the underlying root cause of why they form and how they evolve. We propose that an emphasis on purely performance-based metrics has diluted the community’s understanding of why a certain methodology is (un)successful. Furthermore, the lack of consistent protocols for reporting cell performance and inconsistent terminology for describing physical phenomena that occur at the Li anode make quantitative comparison difficult. The goal of this Perspective is to motivate the need for more consistent and fundamental research on the interfacial electrochemistry on Li metal anodes. Herein we provide an overview of: 1) recent advances in understanding the fundamen...
424 citations
TL;DR: This article asserted that supportive school and classroom climates can positively influence the academic outcomes of students, thus potentially reducing academic achieve and suggested that supportive environments can positively affect academic performance of students in the classroom.
Abstract: Educational researchers and practitioners assert that supportive school and classroom climates can positively influence the academic outcomes of students, thus potentially reducing academic achieve
355 citations
TL;DR: In this paper, the authors reported the highly stable galvanostatic cycling of Li electrodes in a symmetric Li|electrolyte solution|Li coin-cell configuration at a high rate and high areal capacity using fluoroethylene carbonate (FEC)-based electrolyte solutions.
Abstract: We report the highly stable galvanostatic cycling of lithium metal (Li) electrodes in a symmetrical Li|electrolyte solution|Li coin-cell configuration at a high rate and high areal capacity using fluoroethylene carbonate (FEC)-based electrolyte solutions [1 M LiPF6 in FEC/dimethyl carbonate (DMC)]. The FEC-based electrolyte solution shows cycling behavior that is markedly better than that observed for the cells cycled with an ethylene carbonate (EC)-based electrolyte solution (1 M LiPF6 in EC/DMC). With FEC-based electrolyte solution, Li|Li cells can be cycled at 2 mA cm–2 with an areal capacity of 3.3 mAh cm–2 for more than 1100 cycles, and full Li|LiNi0.6Co0.2Mn0.2O2 (NMC) cells with high areal loading cathode demonstrate stable cycling with the same capacity during 90 cycles. An increase in areal capacity up to 6 mA h cm–2 does not affect the shape of the voltage profile of the symmetric Li|Li cells. The reason for this high performance is the formation of a stable and efficient solid electrolyte inter...
TL;DR: In this article, the authors present a short overview and key results of a systematic study of the application of one of the recently most widely investigated components of the electrolyte solutions for lithium-ion batteries, namely, fluoroethylene carbonate (FEC).
Abstract: The performance of lithium-ion batteries (LIBs) depends critically on the nature of the solid–electrolyte interphase (SEI) layers formed on their electrodes surfaces, which are, in turn, defined by the composition of the electrolyte solution. Here, we present a short overview and key results of a systematic study of the application of one of the recently most widely investigated components of the electrolyte solutions for LIBs, namely, fluoroethylene carbonate (FEC). We discuss the benefits of FEC-based electrolyte solutions over the most commonly used ethylene carbonate (EC)-based electrolyte solutions for different LIB systems, including the high-capacity Si anode, high-voltage LiCoPO4 and LiNi0.5Mn1.5O4, Li–sulfur, and other cathodes, as well as full Li-ion cells. Special emphasis is given to the composition and properties of the SEI that is formed on the surface of anodes and cathodes as a result of the electrochemical reduction/oxidation of FEC.
TL;DR: Penicillin has lasting effects in both sexes on gut microbiota, increases cytokine expression in frontal cortex, modifies blood–brain barrier integrity and alters behaviour, and warrants further studies on the potential role of early-life antibiotic use in the development of neuropsychiatric disorders.
Abstract: There is increasing concern about potential long-term effects of antibiotics on children's health. Epidemiological studies have revealed that early-life antibiotic exposure can increase the risk of developing immune and metabolic diseases, and rodent studies have shown that administration of high doses of antibiotics has long-term effects on brain neurochemistry and behaviour. Here we investigate whether low-dose penicillin in late pregnancy and early postnatal life induces long-term effects in the offspring of mice. We find that penicillin has lasting effects in both sexes on gut microbiota, increases cytokine expression in frontal cortex, modifies blood-brain barrier integrity and alters behaviour. The antibiotic-treated mice exhibit impaired anxiety-like and social behaviours, and display aggression. Concurrent supplementation with Lactobacillus rhamnosus JB-1 prevents some of these alterations. These results warrant further studies on the potential role of early-life antibiotic use in the development of neuropsychiatric disorders, and the possible attenuation of these by beneficial bacteria.
30 Oct 2017
TL;DR: A simple zero-knowledge argument protocol for NP whose communication complexity is proportional to the square-root of the verification circuit size, which is attractive not only for very large verification circuits but also for moderately large circuits that arise in applications.
Abstract: We design and implement a simple zero-knowledge argument protocol for NP whose communication complexity is proportional to the square-root of the verification circuit size. The protocol can be based on any collision-resistant hash function. Alternatively, it can be made non-interactive in the random oracle model, yielding concretely efficient zk-SNARKs that do not require a trusted setup or public-key cryptography. Our protocol is attractive not only for very large verification circuits but also for moderately large circuits that arise in applications. For instance, for verifying a SHA-256 preimage in zero-knowledge with 2-40 soundness error, the communication complexity is roughly 44KB (or less than 34KB under a plausible conjecture), the prover running time is 140 ms, and the verifier running time is 62 ms. This proof is roughly 4 times shorter than a similar proof of ZKB++ (Chase et al., CCS 2017), an optimized variant of ZKBoo (Giacomelli et al., USENIX 2016). The communication complexity of our protocol is independent of the circuit structure and depends only on the number of gates. For 2-40 soundness error, the communication becomes smaller than the circuit size for circuits containing roughly 3 million gates or more. Our efficiency advantages become even bigger in an amortized setting, where several instances need to be proven simultaneously. Our zero-knowledge protocol is obtained by applying an optimized version of the general transformation of Ishai et al. (STOC 2007) to a variant of the protocol for secure multiparty computation of Damgard and Ishai (Crypto 2006). It can be viewed as a simple zero-knowledge interactive PCP based on "interleaved" Reed-Solomon codes.
TL;DR: It is shown that a vertical electric field can dynamically extend the photoresponse in a 5 nm-thick BP photodetector from 3.7 to beyond 7.7 μm, opening the doors to various mid-infrared applications.
Abstract: Lately rediscovered orthorhombic black phosphorus (BP) exhibits promising properties for near- and mid-infrared optoelectronics. Although recent electrical measurements indicate that a vertical electric field can effectively reduce its transport bandgap, the impact of the electric field on light-matter interaction remains unclear. Here we show that a vertical electric field can dynamically extend the photoresponse in a 5 nm-thick BP photodetector from 3.7 to beyond 7.7 μm, leveraging the Stark effect. We further demonstrate that such a widely tunable BP photodetector exhibits a peak extrinsic photo-responsivity of 518, 30, and 2.2 mA W-1 at 3.4, 5, and 7.7 μm, respectively, at 77 K. Furthermore, the extracted photo-carrier lifetime indicates a potential operational speed of 1.3 GHz. Our work not only demonstrates the potential of BP as an alternative mid-infrared material with broad optical tunability but also may enable the compact, integrated on-chip high-speed mid-infrared photodetectors, modulators, and spectrometers.
13 Jun 2017
TL;DR: The authors propose to reduce relation extraction to answering simple reading comprehension questions, by associating one or more natural language questions with each relation slot, and show that the approach can generalize to new questions for known relation types with high accuracy, and that zero-shot generalization to unseen relation types is possible, at lower accuracy levels.
Abstract: We show that relation extraction can be reduced to answering simple reading comprehension questions, by associating one or more natural-language questions with each relation slot. This reduction has several advantages: we can (1) learn relation-extraction models by extending recent neural reading-comprehension techniques, (2) build very large training sets for those models by combining relation-specific crowd-sourced questions with distant supervision, and even (3) do zero-shot learning by extracting new relation types that are only specified at test-time, for which we have no labeled training examples. Experiments on a Wikipedia slot-filling task demonstrate that the approach can generalize to new questions for known relation types with high accuracy, and that zero-shot generalization to unseen relation types is possible, at lower accuracy levels, setting the bar for future work on this task.
TL;DR: The results show that GS has significantly expanded its coverage through the years which makes it a powerful database of scholarly literature, however, the quality of resources indexed and overall policy still remains known.
TL;DR: It is suggested that there is no sole, definite answer to the question "how do introns enhance gene expression", rather, each intron-gene combination might undergo its own unique mixture of processes that lead to the perceptible outcome.
TL;DR: The role of brain oscillations in sensory processing is reviewed, and terminology is clarified to distinguish between different phenomena that are often lumped together as reflecting “neural entrainment” but may actually vary in their mechanistic underpinnings.
TL;DR: This tutorial provides a guide to how to write simulators and prove security via the simulation paradigm, and assumes some familiarity with the notions of secure encryption, zero-knowledge, and secure computation.
Abstract: One of the most fundamental notions of cryptography is that of simulation. It stands behind the concepts of semantic security, zero knowledge, and security for multiparty computation. However, writing a simulator and proving security via the use of simulation is a nontrivial task, and one that many newcomers to the field often find difficult. In this tutorial, we provide a guide to how to write simulators and prove security via the simulation paradigm. Although we have tried to make this tutorial as stand-alone as possible, we assume some familiarity with the notions of secure encryption, zero-knowledge, and secure computation.
TL;DR: It is shown that RNA editing is particularly common in behaviorally sophisticated coleoid cephalopods, with tens of thousands of evolutionarily conserved sites, highlighting the importance of RNA recoding as a strategy for diversifying proteins, particularly those associated with neural function.
Columbia University1, University of Washington2, Google3, University of Science and Technology of China4, University of California, Berkeley5, Monash University6, Cornell University7, New York University8, University of Michigan9, University of British Columbia10, University of Freiburg11, Oregon Health & Science University12, Massachusetts Institute of Technology13, Harvard University14, Hastings Center15, University of Wisconsin-Madison16, Bar-Ilan University17, University of Maryland, College Park18, University of Pennsylvania19
TL;DR: Artificial intelligence and brain–computer interfaces must respect and preserve people's privacy, identity, agency and equality, say Rafael Yuste, Sara Goering and colleagues.
Abstract: Artificial intelligence and brain–computer interfaces must respect and preserve people's privacy, identity, agency and equality, say Rafael Yuste, Sara Goering and colleagues.
Austrian Institute of Technology1, Johns Hopkins University2, Utrecht University3, Ford Motor Company4, Bar-Ilan University5, ReNeuron6, Karolinska Institutet7, Paracelsus Private Medical University of Salzburg8, Salk Institute for Biological Studies9, National Tsing Hua University10, Royal Brisbane and Women's Hospital11, Hiroshima University12, National University of Singapore13, Tufts University14, Guangzhou Institutes of Biomedicine and Health15, Agency for Science, Technology and Research16, Tsinghua University17, University of Duisburg-Essen18
TL;DR: A review outlines topic‐specific action items that, if addressed, will enhance the development of best‐practice models for EV therapies and help to standardization and coordination of development efforts.
Abstract: Growing interest in extracellular vesicles (EVs, including exosomes and microvesicles) as therapeutic entities, particularly in stem cell-related approaches, has underlined the need for standardization and coordination of development efforts. Members of the International Society for Extracellular Vesicles and the Society for Clinical Research and Translation of Extracellular Vesicles Singapore convened a Workshop on this topic to discuss the opportunities and challenges associated with development of EV-based therapeutics at the preclinical and clinical levels. This review outlines topic-specific action items that, if addressed, will enhance the development of best-practice models for EV therapies. Stem Cells Translational Medicine 2017;6:1730-1739.
TL;DR: A highly discriminative and robust model is obtained, with an area under the curve of 0.95, for the iterative stochastic elimination optimization technique, used to build predictive models and to index natural products for their anticancer bioactivity.
Abstract: Cancer is considered one of the primary diseases that cause morbidity and mortality in millions of people worldwide and due to its prevalence, there is undoubtedly an unmet need to discover novel anticancer drugs. However, the traditional process of drug discovery and development is lengthy and expensive, so the application of in silico techniques and optimization algorithms in drug discovery projects can provide a solution, saving time and costs. A set of 617 approved anticancer drugs, constituting the active domain, and a set of 2,892 natural products, constituting the inactive domain, were employed to build predictive models and to index natural products for their anticancer bioactivity. Using the iterative stochastic elimination optimization technique, we obtained a highly discriminative and robust model, with an area under the curve of 0.95. Twelve natural products that scored highly as potential anticancer drug candidates are disclosed. Searching the scientific literature revealed that few of those molecules (Neoechinulin, Colchicine, and Piperolactam) have already been experimentally screened for their anticancer activity and found active. The other phytochemicals await evaluation for their anticancerous activity in wet lab.
TL;DR: These findings link brain-to-brain synchrony to the degree of social connectedness among interacting partners, ground neural synchrony in key nonverbal social behaviors, and highlight the role of human attachment in providing a template for two-brain coordination.
Abstract: The evolution of humans as a highly social species tuned the brain to the social world; yet the mechanisms by which humans coordinate their brain response online during social interactions remain unclear. Using hyperscanning EEG recordings, we measured brain-to-brain synchrony in 104 adults during a male-female naturalistic social interaction, comparing romantic couples and strangers. Neural synchrony was found for couples, but not for strangers, localized to temporal-parietal structures and expressed in gamma rhythms. Brain coordination was not found during a three-minute rest, pinpointing neural synchrony to social interactions among affiliative partners. Brain-to-brain synchrony was linked with behavioral synchrony. Among couples, neural synchrony was anchored in moments of social gaze and positive affect, whereas among strangers, longer durations of social gaze and positive affect correlated with greater neural synchrony. Brain-to-brain synchrony was unrelated to episodes of speech/no-speech or general content of conversation. Our findings link brain-to-brain synchrony to the degree of social connectedness among interacting partners, ground neural synchrony in key nonverbal social behaviors, and highlight the role of human attachment in providing a template for two-brain coordination.
TL;DR: Regardless of how signals move from cell to cell, they help prepare distant parts of the plant for impending challenges from specific biotic or abiotic stresses.
Abstract: Plants show a rapid systemic response to a wide range of environmental stresses, where the signals from the site of stimulus perception are transmitted to distal organs to elicit plant-wide responses. A wide range of signaling molecules are trafficked through the plant, but a trio of potentially interacting messengers, reactive oxygen species (ROS), Ca2+ and electrical signaling ('trio signaling') appear to form a network supporting rapid signal transmission. The molecular components underlying this rapid communication are beginning to be identified, such as the ROS producing NAPDH oxidase RBOHD, the ion channel two pore channel 1 (TPC1), and glutamate receptor-like channels GLR3.3 and GLR3.6. The plant cell wall presents a plant-specific route for possible propagation of signals from cell to cell. However, the degree to which the cell wall limits information exchange between cells via transfer of small molecules through an extracellular route, or whether it provides an environment to facilitate transmission of regulators such as ROS or H+ remains to be determined. Similarly, the role of plasmodesmata as both conduits and gatekeepers for the propagation of rapid cell-to-cell signaling remains a key open question. Regardless of how signals move from cell to cell, they help prepare distant parts of the plant for impending challenges from specific biotic or abiotic stresses.
TL;DR: A growing body of leadership literature focuses on leader and follower identity dynamics, levels, processes of development and outcomes Despite the importance of the phenomena, there has been surprisingly little effort to systematically review the widely dispersed literature.
Abstract: A growing body of leadership literature focuses on leader and follower identity dynamics, levels, processes of development and outcomes Despite the importance of the phenomena, there has been surprisingly little effort to systematically review the widely dispersed literature on leader and follower identity In this review we map existing studies on a multilevel framework that integrates levels-of-the self (individual, relational and collective) with the levels-of-analysis (intrapersonal, interpersonal and group) on which leader or follower identity work takes place We also synthesize work from multiple research paradigms, such as social psychology experimental studies, narrative accounts of leaders' identity work and field studies on antecedents, outcomes, mediating mechanisms and boundary conditions Finally, we outline implications for leadership development and call attention to key themes we see ripe for future research
01 Jan 2017
TL;DR: Set and setting is a term which refers to the psychological, social, and cultural parameters which shape the response to psychedelic drugs as discussed by the authors, and it is considered fundamental to psychedelic rese...
Abstract: Set and setting is a term which refers to the psychological, social, and cultural parameters which shape the response to psychedelic drugs. The concept is considered fundamental to psychedelic rese...
TL;DR: Nm-seq uncovered thousands of Nm sites in human mRNA with features suggesting functional roles, and leveraged the differential reactivity of 2′-O-methylated and2′-hydroxylated nucleosides to periodate oxidation to develop Nm- sequencing, a sensitive method for transcriptome-wide mapping of Nn with base precision.
Abstract: The ribose of RNA nucleotides can be 2'-O-methylated (Nm). Despite advances in high-throughput detection, the inert chemical nature of Nm still limits sensitivity and precludes mapping in mRNA. We leveraged the differential reactivity of 2'-O-methylated and 2'-hydroxylated nucleosides to periodate oxidation to develop Nm-seq, a sensitive method for transcriptome-wide mapping of Nm with base precision. Nm-seq uncovered thousands of Nm sites in human mRNA with features suggesting functional roles.