Neural Programming by Example

Programming by Example (PBE) targets at automatically inferring a computer program for accomplishing a certain task from sample input and output. In this paper, we propose a deep neural networks (DNN) based PBE model called Neural Programming by Example (NPBE), which can learn from input-output strings and induce programs that solve the string manipulation problems. Our NPBE model has four neural network based components: a string encoder, an input-output analyzer, a program generator, and a symbol selector. We demonstrate the effectiveness of NPBE by training it end-to-end to solve some common string manipulation problems in spreadsheet systems. The results show that our model can induce string manipulation programs effectively. Our work is one step towards teaching DNN to generate computer programs.Comment: 7 pages, Association for the Advancement of Artificial Intelligence (AAAI

Fabrication and Characterization of In Situ Synthesized SiC/Al Composites by Combustion Synthesis and Hot Press Consolidation Method

The in situ SiC/Al composites were fabricated in Al-Si-C systems with different Si/C mass ratios and holding time by the method of combustion synthesis and hot press consolidation. The influences of Si/C mass ratio and holding time on the phase constitution, microstructure, and hardness of the composites were investigated. The results indicate that the increase of Si/C mass ratio leads to more uniform size distribution of the SiC particles in the Al matrix. Moreover, by improving the Si/C mass ratio from 4 : 1 to 5 : 1, the maximum size of SiC particle was reduced from 4.1 μm to 2.0 μm. Meanwhile, the percentage of submicroparticles was increased from 22% to 63%, and the average hardness value of the composites was increased by 13%. In addition, when the holding time is set to be fifteen minutes, the Al4C3 phase did not exist in the composites because of its total reactions with Si atoms to form SiC particles, and the average hardness value was 73.8 HB

Using Graphs to Characterize Nationwide Physician Referral Networks

AIM: Evaluating physician referral network characteristics can help to understand how physicians and hospitals interact to provide patient services within the US healthcare system and ultimately how this may influence patient outcomes. METHOD: We used the 2012-2013 national Physician Referral data from the Centers for Medicare & Medicaid Services (CMS), which consists of 73,071,804 pairs of referrals from one health provider to another in calendar year 2012 and the first two quarters of year 2013 within 30 days of care. These referrals are from 642,144 national-wide physicians and 4,811 hospitals. We obtained information for each provider, physician or hospital, from CMS. We then generated a nationwide referral network. We described the network with graphs and potential important network characteristics using graph theory and social network theory. Further, we described the sub-network by Exponential random graph models (ERGM). The ERGM coefficients from such models can reflect the properties of the network nodes and help illustrate how the network outcomes are influenced. RESULTS: Our results show that 1) the graphs and characteristics vary substantially across the geographic areas and 2) graphs and the characteristics depicting the same area are strongly associated. The ERGM model shows that physicians in cardiology, diagnostic radiology and geriatric medicine are more likely to send and receive referrals than physicians in family care and internal medicine in certain hospitals. CONCLUSION: We demonstrate the use of graph-based approaches to describe and evaluate nationwide physician referral networks. Further work will study how these network characteristics are associated with hospital outcomes

Psychological Capital, Positive Affect, and Organizational Outcomes: A Three-Wave Cross-Lagged Study

Psychological capital (PsyCap) is a higher-order construct comprising hope, efficacy, optimism, and resiliency, which has attracted more and more attention from both academics and practitioners. Despite promising progress made in the PsyCap literature, the underlying mechanisms linking PsyCap to organizational outcomes still need more investigation utilizing longitudinal research design. Moreover, the reciprocal relationships between PsyCap and positive affect require more attention. Therefore, we aim to test the central role of positive affect in the relationships between PsyCap and affective organizational commitment (AOC) on one hand and organizational citizenship behaviour toward organization (OCBO) on the other hand as well as the reciprocal relationships between PsyCap and positive affect in this study. A three-wave longitudinal survey was conducted using a cross-lagged panel design with a one-month time lag between two consecutive waves. Panel data was collected from 208 workers in Beijing, China. The results support the hypothesis that positive affect serves as a mediator in the relationships between PsyCap and OCBO. Moreover, we also find some support for a reciprocal relationship between PsyCap and positive affect. The theoretical and practical implications of the findings are also discussed

Rapid Estimation of Binding Activity of Influenza Virus Hemagglutinin to Human and Avian Receptors

A critical step for avian influenza viruses to infect human hosts and cause epidemics or pandemics is acquisition of the ability of the viral hemagglutinin (HA) to bind to human receptors. However, current global influenza surveillance does not monitor HA binding specificity due to a lack of rapid and reliable assays. Here we report a computational method that uses an effective scoring function to quantify HA-receptor binding activities with high accuracy and speed. Application of this method reveals receptor specificity changes and its temporal relationship with antigenicity changes during the evolution of human H3N2 viruses. The method predicts that two amino acid differences at 222 and 225 between HAs of A/Fujian/411/02 and A/Panama/2007/99 viruses account for their differences in binding to both avian and human receptors; this prediction was verified experimentally. The new computational method could provide an urgently needed tool for rapid and large-scale analysis of HA receptor specificities for global influenza surveillance.National Key Project (2008ZX10004-013)National Institutes of Health (U.S.) (grant AI07443)Singapore-MIT Alliance for Research and TechnologyMassachusetts Institute of Technology. International Science and Technology Initiatives Global Seed FundNational Basic Research Program (973 Program) (2009CB918503)National Basic Research Program (973 Program) (2006CB911002

A critical survey of technologies of large offshore wind farm integration : summary, advances, and perspectives

Offshore wind farms (OWFs) have received widespread attention for their abundant unexploited wind energy potential and convenient locations conditions. They are rapidly developing towards having large capacity and being located further away from shore. It is thus necessary to explore effective power transmission technologies to connect large OWFs to onshore grids. At present, three types of power transmission technologies have been proposed for large OWF integration. They are: high voltage alternating current (HVAC) transmission, high voltage direct current (HVDC) transmission, and low-frequency alternating current (LFAC) or fractional frequency alternating current transmission. This work undertakes a comprehensive review of grid connection technologies for large OWF integration. Compared with previous reviews, a more exhaustive summary is provided to elaborate HVAC, LFAC, and five HVDC topologies, consisting of line-commutated converter HVDC, voltage source converter HVDC, hybrid-HVDC, diode rectifier-based HVDC, and all DC transmission systems. The fault ride-through technologies of the grid connection schemes are also presented in detail to provide research references and guidelines for researchers. In addition, a comprehensive evaluation of the seven grid connection technologies for large OWFs is proposed based on eight specific indicators. Finally, eight conclusions and six perspectives are outlined for future research in integrating large OWFs

BGI-RIS: An integrated information resource and comparative analysis workbench for rice genomics

Rice is a major food staple for the world's population and serves as a model species in cereal genome research. The Beijing Genomics Institute (BGI) has long been devoting itself to sequencing, information analysis and biological research of the rice and other crop genomes. In order to facilitate the application of the rice genomic information and to provide a foundation for functional and evolutionary studies of other important cereal crops, we implemented our Rice Information System (BGI-RIS), the most up-to-date integrated information resource as well as a workbench for comparative genomic analysis. In addition to comprehensive data from Oryza sativa L. ssp. indica sequenced by BGI, BGI-RIS also hosts carefully curated genome information from Oryza sativa L. ssp. japonica and EST sequences available from other cereal crops. In this resource, sequence contigs of indica (93-11) have been further assembled into Mbp-sized scaffolds and anchored onto the rice chromosomes referenced to physical/genetic markers, cDNAs and BAC-end sequences. We have annotated the rice genomes for gene content, repetitive elements, gene duplications (tandem and segmental) and single nucleotide polymorphisms between rice subspecies. Designed as a basic platform, BGI-RIS presents the sequenced genomes and related information in systematic and graphical ways for the convenience of in-depth comparative studie

Rice consumption and risk of cardiovascular disease: results from a pooled analysis of 3 U.S. cohorts.

BACKGROUND: Health concerns have been raised about rice consumption, which may significantly contribute to arsenic exposure. However, little is known regarding whether habitual rice consumption is associated with cardiovascular disease (CVD) risk. OBJECTIVE: We examined prospectively the association of white rice and brown rice consumption with CVD risk. DESIGN: We followed a total of 207,556 women and men [73,228 women from the Nurses' Health Study (1984-2010), 92,158 women from the Nurses' Health Study II (1991-2011), and 42,170 men from the Health Professionals Follow-Up Study (1986-2010)] who were free of CVD and cancer at baseline. Validated semiquantitative food-frequency questionnaires were used to assess consumption of white rice, brown rice, and other food items. Fatal and nonfatal CVD (coronary artery disease and stroke) was confirmed by medical records or self-reports. RESULTS: During 4,393,130 person-years of follow-up, 12,391 cases of CVD were identified. After adjustment for major CVD risk factors, including demographics, lifestyle, and other dietary intakes, rice consumption was not associated with CVD risk. The multivariable-adjuted HR of developing CVD comparing ≥5 servings/wk with <1 serving/wk was 0.98 (95% CI: 0.84, 1.14) for white rice, 1.01 (0.79, 1.28) for brown rice, and 0.99 (0.90, 1.08) for total rice. To minimize the potential impact of racial difference in rice consumption, we restricted the analyses to whites only and obtained similar results: the HRs of CVD for ≥5 servings/wk compared with <1 serving/wk were 1.04 (95% CI: 0.88, 1.22) for white rice and 1.01 (0.78, 1.31) for brown rice. CONCLUSIONS: Greater habitual consumption of white rice or brown rice is not associated with CVD risk. These findings suggest that rice consumption may not pose a significant CVD risk among the U.S. population when consumed at current amounts. More prospective studies are needed to explore these associations in other populations.Supported by NIH grants CA50385, CA87969, CA176726, CA167552, HL60712, HL034594, HL088521, and HL35464. QS was supported by a career development grant R00HL098459 sponsored by the National Heart, Lung, and Blood Institute. FI was supported by Medical Research Council Epidemiology Unit Core Support (MC_UU_12015/5).This article was originally published in The American Journal of Clinical Nutrition (I Muraki, H Wu, F Imamura, F Laden, EB Rimm, FB Hu, WC Willett, Q Sun, The American Journal of Clinical Nutrition 2015, 101, 164-172

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected