Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Decoding in Sequence Models using Discrete Latent Variables

Autoregressive sequence models based on deep neural networks, such as RNNs, Wavenet and the Transformer attain state-of-the-art results on many tasks. However, they are difficult to parallelize and are thus slow at processing long sequences. RNNs lack parallelism both during training and decoding, while architectures like WaveNet and Transformer are much more parallelizable during training, yet still operate sequentially during decoding. Inspired by [arXiv:1711.00937], we present a method to extend sequence models using discrete latent variables that makes decoding much more parallelizable. We first auto-encode the target sequence into a shorter sequence of discrete latent variables, which at inference time is generated autoregressively, and finally decode the output sequence from this shorter latent sequence in parallel. To this end, we introduce a novel method for constructing a sequence of discrete latent variables and compare it with previously introduced methods. Finally, we evaluate our model end-to-end on the task of neural machine translation, where it is an order of magnitude faster at decoding than comparable autoregressive models. While lower in BLEU than purely autoregressive models, our model achieves higher scores than previously proposed non-autoregressive translation models.
The Use of Agro Waste Alpinia galanga Fibers as Reinforcement in Polyethylene Composites

Employing fibers particularly those from renewable materials as an alternative to inorganic fibers in composites is part of the effort to promote bio-based products as well as to broaden recycling of solid wastes. In this work, the use of agro waste Alpinia galanga (AG) as composite reinforcement was investigated in terms of tensile properties, thermal stability, morphology and water absorption. Composites based on AG fibers and high density polyethylene (HDPE) were prepared together with an additive, eco- degradant (ECO) and a compatibilizer, polyethylene-g-maleic anhydride (PE-g-MA) in a mixer, Brabender Plastograph EC at various AG fiber loadings. The results reveal that the composite formulation enabled AG fibers to function as reinforcement in HDPE-based composites. The presence of ECO at 15 wt% fiber loading improved tensile strength up to 33.6 MPa, about 21 % higher than that of pristine HDPE (27.8 MPa). The addition of MA-g-PE at 10 wt% fiber loading also indicates comparable tensile strength to pristine HDPE of about 27.5 MPa. The Young's modulus of AG/HDPE composites with the addition of ECO was enhanced up to 4874 MPa as compared to 1012 MPa of pristine HDPE. The elongation at break of the AG/HDPE composites however is somewhat lower than that of pristine HDPE. The water absorption of AG/HDPE composites with ECO at 15 wt% fiber loading was improved to 0.96 % as compared to 1.40% of the AG/HDPE composites. The proposed formulation containing ECO and PE-g- MA also slightly improved thermal stability of AG/HDPE composites. Scanning electron microscopy examination indicates a much better adhesion between AG fibers and HDPE matrix with the presence of ECO. The composite formulation with ECO, an environment-friendly additive which helps degrade polyolefin composites to the basic elements with no harmful effects contributed to noticeable improvements in properties of AG/HDPE composites.
High-order volterra series analysis using parallel computing

SUMMARY The paper addresses the determination of high order Volterra transfer functions of non-linear mul-tiport networks containing multidimensional non-linear elements. A new method is developed for utilizing parallel computing which is very efficient for approximately 10–20 processors. The utilization of each processor may be as high as 80–95 %. The developed program is very flexible as it is ANSI C++ compatible and it may run on both single and multiprocessor computers. Using about 8 processors it is possible to analyze rather complicated nonlinear circuits up to 9th order in a few hours.
Enhanced electrochemical performance of PEDOT film incorporating PEDOT:PSS

For effective use of conducting polymers, a hybrid film composed of poly (3,4-ethylenedioxythiophene) : poly (styrenesulfonate) (PEDOT:PSS) and poly (3,4-ethylenedioxythiophene) (PEDOT) has been fabricated by a in situ polymerization method. Each component in the hybrid film provides unique and crucial function to achieve optimized electrochemical properties. In the presence of PEDOT:PSS, the PS/PEDOT hybrid film is found to possess the better energy storage ability. Volumetric capacity of composite film (97.51 F/cm 3 ) is much higher than that of pure PEDOT:PSS (37.75 F/cm 3 ) and PEDOT (50.52 F/cm 3 ) films. The hybrid film also exhibits excellent charge/discharge rate and good cycling stability, retaining 92.4% of its initial charge after 1000 cycles. The electrochemical performance improvement is primarily due to the synergistic effect between PEDOT:PSS and PEDOT. It is anticipated that this flexible procedure could be a promising large scale fabrication method for supercapacitor electrodes.
Slow Loris Trade in Vietnam: Exploring Diverse Knowledge and Values

Wildlife trade can present a major threat to primate populations. In Vietnam, slow lorises (genus Nycticebus) are subject to local, regional and international demand for diverse uses including as medicine, as meat and for pets. Ethnographic approaches explore the nuances of human-primate interactions in complex sociocultural contexts. We combined ethnographic interviews of key informants with information from questionnaires, focus groups and a movie broadcast on Vietnamese television to explore diverse knowledge and values related to slow lorises and their use in trade in Vietnam. We infer prices, uses and networks for expanding targeted regional and international markets as compared to the opportunistic local one. We highlight key findings related to gendered knowledge about slow lorises and more-than-human ontologies of slow lorises as active participants in human-slow loris interactions. We suggest that conservation efforts should pay attention to the clarification of vernacular names, and use names that highlight ecological or behavioural qualities of slow lorises, rather than other names that could be confused with medicinal remedies. Our results confirm the dynamic complexity of trade in Vietnam, highlighting the importance of ethnographic methods to explore diverse knowledge and values for place-based or site-appropriate conservation management of primates and other highly traded taxa.
Insights from agriculture for the management of insecticide resistance in disease vectors

Key to contemporary management of diseases such as malaria, dengue, and filariasis is control of the insect vectors responsible for transmission. Insecticide‐based interventions have contributed to declines in disease burdens in many areas, but this progress could be threatened by the emergence of insecticide resistance in vector populations. Insecticide resistance is likewise a major concern in agriculture, where insect pests can cause substantial yield losses. Here, we explore overlaps between understanding and managing insecticide resistance in agriculture and in public health. We have used the Global Plan for Insecticide Resistance Management in malaria vectors, developed under the auspices of the World Health Organization Global Malaria Program, as a framework for this exploration because it serves as one of the few cohesive documents for managing a global insecticide resistance crisis. Generally, this comparison highlights some fundamental differences between insect control in agriculture and in public health. Moreover, we emphasize that the success of insecticide resistance management strategies is strongly dependent on the biological specifics of each system. We suggest that the biological, operational, and regulatory differences between agriculture and public health limit the wholesale transfer of knowledge and practices from one system to the other. Nonetheless, there are some valuable insights from agriculture that could assist in advancing the existing Global Plan for Insecticide Resistance Management framework.
Facet-specific interaction between methanol and TiO2 probed by sum-frequency vibrational spectroscopy

Significance Facet engineering has become a major strategy for designing crystalline catalysts, yet many fundamental issues, including facet-specific interaction with adsorbates, remain unsolved due to lack of experimental investigation. Using surface-specific sum-frequency vibrational spectroscopy, we have conducted an in-depth study of methanol adsorption on four different facets of TiO2 under ambient conditions. The spectra revealed that for the four facets investigated, dissociation of adsorbed methanol occurs only when surface defects are present. Adsorption kinetics and energetics appeared nearly the same on different facets, but the Fermi resonance coupling strength for CH3 of adsorbed methanol was found to depend sensitively on facets and methanol coverage, and could serve as a gauge for studying facet effects on molecular adsorption and surface reactions. The facet-specific interaction between molecules and crystalline catalysts, such as titanium dioxides (TiO2), has attracted much attention due to possible facet-dependent reactivity. Using surface-sensitive sum-frequency vibrational spectroscopy, we have studied how methanol interacts with different common facets of crystalline TiO2, including rutile(110), (001), (100), and anatase(101), under ambient temperature and pressure. We found that methanol adsorbs predominantly in the molecular form on all of the four surfaces, while spontaneous dissociation into methoxy occurs preferentially when these surfaces become defective. Extraction of Fermi resonance coupling between stretch and bending modes of the methyl group in analyzing adsorbed methanol spectra allows determination of the methanol adsorption isotherm. The isotherms obtained for the four surfaces are nearly the same, yielding two adsorbed Gibbs free energies associated with two different adsorption configurations singled out by ab initio calculations. They are (i) ∼−20 kJ/mol for methanol with its oxygen attached to a low-coordinated surface titanium, and (ii) ∼−5 kJ/mol for methanol hydrogen-bonded to a surface oxygen and a neighboring methanol molecule. Despite similar adsorption energetics, the Fermi resonance coupling strength for adsorbed methanol appears to depend sensitively on the surface facet and coverage.
Using EEG to Predict Consumers’ Future Choices

It is well established that neural imaging technology can predict preferences for consumer products. However, the applicability of this method to consumer marketing research remains uncertain, partly because of the expense required. In this article, the authors demonstrate that neural measurements made with a relatively low-cost and widely available measurement method—electroencephalography (EEG)—can predict future choices of consumer products. In the experiment, participants viewed individual consumer products in isolation, without making any actual choices, while their neural activity was measured with EEG. At the end of the experiment, participants were offered choices between pairs of the same products. The authors find that neural activity measured from a midfrontal electrode displays an increase in the N200 component and a weaker theta band power that correlates with a more preferred product. Using recent techniques for relating neural measurements to choice prediction, they demonstrate that these measures predict subsequent choices. Moreover, the accuracy of prediction depends on both the ordinal and cardinal distance of the EEG data; the larger the difference in EEG activity between two products, the better the predictive accuracy.
For They Know Not What They Do Selection through Incentives when Information is Costly PRELIMINARY AND INCOMPLETE

Who participates in transactions when information about their consequences must be learned? Theoretically, we show that decision makers for whom acquiring and processing information is more costly respond more strongly to changes in incentives for participating, and decide to participate based on worse information. Consequently, with higher incentives, the pool of participants consists of a larger fraction of individuals with a worse understanding of the consequences of their decision. Our behavioral experiment confirms these predictions, both for experimental variation in the costs of information acquisition, and for various measures of information costs including school grades and cognitive ability. These findings are relevant for any transaction that combines a price paid for participation with uncertain yet learnable consequences. Our results also clarify the relation between incentives and the ethical principle of informed consent, and thus help address ethical concerns with incentives. ∗Ambuehl: University of Toronto, UTSC and Rotman School of Management, 105 St George Street, Toronto, ON M5S 3E6, Canada, sandro.ambuehl@utoronto.ca. Ockenfels: University of Cologne, Department of Economics, Universitätsstrasse 22a, 50923 Cologne, Germany, ockenfels@uni-koeln.de. Stewart: University of Toronto, Department of Economics, 150 St. George Street, Toronto, ON M5S 3G7, Canada, colinbstewart@gmail.com. We are grateful to Roland Bénabou, Yoram Halevy, Collin Raymond, Roberto Weber and seminar and conference participants at Bonn, Calgary, Frankfurt, the FTC, Montreal, Ottawa, Purdue, Toronto, the CESifo Behavioural Economics Conference, the North American ESA Conference, SITE, and the Vienna Behavioral Public Economics Workshop for helpful comments and suggestions. This research has been approved by the University of Toronto’s Research Ethics Board in protocol 34310. Viola S. Ackfeld, Rami Abou-Seido and Ruizhi Zhu provided helpful research assistance. Ockenfels gratefully acknowledges support by the German Science Foundation through the DFG Research Unit Design & Behavior (FOR 1371). Ambuehl gratefully acknowledges support through a University of Toronto Connaught New Researcher Award and the Wynne and Bertil Plumptre Fellowship at the University of Toronto Scarborough. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 741409); the results reflect the authors’ view, the ERC is not responsible for any use that may be made of the information it contains.
TopP–S: Persistent homology‐based multi‐task deep neural networks for simultaneous predictions of partition coefficient and aqueous solubility

Aqueous solubility and partition coefficient are important physical properties of small molecules. Accurate theoretical prediction of aqueous solubility and partition coefficient plays an important role in drug design and discovery. The prediction accuracy depends crucially on molecular descriptors which are typically derived from a theoretical understanding of the chemistry and physics of small molecules. This work introduces an algebraic topology‐based method, called element‐specific persistent homology (ESPH), as a new representation of small molecules that is entirely different from conventional chemical and/or physical representations. ESPH describes molecular properties in terms of multiscale and multicomponent topological invariants. Such topological representation is systematical, comprehensive, and scalable with respect to molecular size and composition variations. However, it cannot be literally translated into a physical interpretation. Fortunately, it is readily suitable for machine learning methods, rendering topological learning algorithms. Due to the inherent correlation between solubility and partition coefficient, a uniform ESPH representation is developed for both properties, which facilitates multi‐task deep neural networks for their simultaneous predictions. This strategy leads to a more accurate prediction of relatively small datasets. A total of six datasets is considered in this work to validate the proposed topological and multitask deep learning approaches. It is demonstrated that the proposed approaches achieve some of the most accurate predictions of aqueous solubility and partition coefficient. Our software is available online at http://weilab.math.msu.edu/TopP-S/. © 2018 Wiley Periodicals, Inc.
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions

In the recent literature the important role of depth in deep learning has been emphasized. In this paper we argue that sufficient width of a feedforward network is equally important by answering the simple question under which conditions the decision regions of a neural network are connected. It turns out that for a class of activation functions including leaky ReLU, neural networks having a pyramidal structure, that is no layer has more hidden units than the input dimension, produce necessarily connected decision regions. This implies that a sufficiently wide hidden layer is necessary to guarantee that the network can produce disconnected decision regions. We discuss the implications of this result for the construction of neural networks, in particular the relation to the problem of adversarial manipulation of classifiers.
Sympatric serpentine endemic Monardella (Lamiaceae) species maintain habitat differences despite hybridization

Ecological differentiation and genetic isolation are thought to be critical in facilitating coexistence between related species, but the relative importance of these phenomena and the interactions between them are not well understood. Here, we examine divergence in abiotic habitat affinity and the extent of hybridization and introgression between two rare species of Monardella (Lamiaceae) that are both restricted to the same serpentine soil exposure in California. Although broadly sympatric, they are found in microhabitats that differ consistently in soil chemistry, slope, rockiness and vegetation. We identify one active hybrid zone at a site with intermediate soil and above‐ground characteristics, and we document admixture patterns indicative of extensive and asymmetric introgression from one species into the other. We find that genetic distance among heterospecific populations is related to geographic distance, such that the extent of apparent introgression is partly explained by the spatial proximity to the hybrid zone. Our work shows that plant species can maintain morphological and ecological integrity in the face of weak genetic isolation, intermediate habitats can facilitate the establishment of hybrids, and that the degree of apparent introgression a population experiences is related to its geographic location rather than its local habitat characteristics.
Is mean platelet volume a better biomarker in pre‐eclampsia?

Platelet activation and destruction is a well recognized feature of pre‐eclampsia, but the current literature is contradictory regarding the role of mean platelet volume (MPV) in the diagnosis of this condition. We investigated whether MPV, compared with other routine laboratory markers such as platelet count, is a more significant biomarker of pre‐eclampsia, giving special attention to the intrapartum period.
Optical characterization of inhomogeneities in blue-emitting InGaN/GaN MQWs

CHENG LI. Optical characterization of inhomogeneities in blue-emitting InGaN/GaN MQWs. (Under the direction of DR. EDWARD B. STOKES) The growth of blue-emitting InGaN/GaN MQWs, the system setup of a low temperature PL/EL/IV system for temperature dependent PL/EL/IV spectroscopy, and the system setup of a CLSM with nanometer-scale spectrum measurement and TRPL measurement abilities are described. A range of temperature-dependent PL experimental work, CLSM imaging experimental work and TRPL experimental work on blue-emitting InGaN/GaN MQWs are presented. In temperature-dependent PL measurements, the decreasing of spectrumintegrated PL intensity with increasing temperature is explained with a two-nonradiativechannel model, in which the two nonradiative channels correspond to the thermal activation of carriers out of the strongly localized states and the weakly localized states, respectively. The ‘S-shaped’ red-blue-red shift of PL peak energy and the ‘inverse Sshaped’ change of PL FWHM when temperature increases from 10 K to 300 K are explained with carrier localization and carrier dynamics. CLSM imaging and nanometer-scale PL spectral measurements show that the PL intensity fluctuates in micrometer scale, and that the bandgap energy in bright region is tens of meV smaller than that in dark region. The small-bandgap-energy regions are localization centers which limit the diffusion of the carriers and prevent carriers from diffusing to the NRRCs. Nanometer-scale TRPL measurements are conducted on blue-emitting InGaN/GaN MQWs for the first time, as far as the author knows. The measurements
Species richness alone does not predict cultural ecosystem service value

Significance Sustaining biodiversity and ecosystem services are common conservation goals. However, understanding relationships between biodiversity and cultural ecosystem services (CES) and determining the best indicators to represent CES remain crucial challenges. We combined ecological and social data to compare CES value of wildflower communities based on observed species richness versus revealed social preferences. Using a discrete-choice experiment with images of wildflower communities, we analyzed which aspects of biodiversity were associated with the aesthetic preferences of forest visitors. Although commonly used to indicate biodiversity-based CES, species richness did not predict aesthetic preference. This study suggests that successful management of CES requires understanding stakeholders’ preferences to determine conservation priorities. Many biodiversity-ecosystem services studies omit cultural ecosystem services (CES) or use species richness as a proxy and assume that more species confer greater CES value. We studied wildflower viewing, a key biodiversity-based CES in amenity-based landscapes, in Southern Appalachian Mountain forests and asked (i) How do aesthetic preferences for wildflower communities vary with components of biodiversity, including species richness? ; (ii) How do aesthetic preferences for wildflower communities vary across psychographic groups? ; and (iii) How well does species richness perform as an indicator of CES value compared with revealed social preferences for wildflower communities? Public forest visitors (n = 293) were surveyed during the summer of 2015 and asked to choose among images of wildflower communities in which flower species richness, flower abundance, species evenness, color diversity, and presence of charismatic species had been digitally manipulated. Aesthetic preferences among images were unrelated to species richness but increased with more abundant flowers, greater species evenness, and greater color diversity. Aesthetic preferences were consistent across psychographic groups and unaffected by knowledge of local flora or value placed on wildflower viewing. When actual wildflower communities (n = 54) were ranked based on empirically measured flower species richness or wildflower viewing utility based on multinomial logit models of revealed preferences, rankings were broadly similar. However, designation of hotspots (CES values above the median) based on species richness alone missed 27% of wildflower viewing utility hotspots. Thus, conservation priorities for sustaining CES should incorporate social preferences and consider multiple dimensions of biodiversity that underpin CES supply.