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22 pags., 8 figs., 1 tab., Massive stars disrupt their natal molecular cloud material through radiative and mechanical feedback processes. These processes have profound effects on the evolution of interstellar matter in our Galaxy and throughout the universe, from the era of vigorous star formation at redshifts of 1-3 to the present day. The dominant feedback processes can be probed by observations of the Photo-Dissociation Regions (PDRs) where the far-ultraviolet photons of massive stars create warm regions of gas and dust in the neutral atomic and molecular gas. PDR emission provides a unique tool to study in detail the physical and chemical processes that are relevant for most of the mass in inter-and circumstellar media including diffuse clouds, proto-planetary disks, and molecular cloud surfaces, globules, planetary nebulae, and star-forming regions. PDR emission dominates the infrared (IR) spectra of star-forming galaxies. Most of the Galactic and extragalactic observations obtained with the James Webb Space Telescope (JWST) will therefore arise in PDR emission. In this paper we present an Early Release Science program using the MIRI, NIRSpec, and NIRCam instruments dedicated to the observations of an emblematic and nearby PDR: the Orion Bar. These early JWST observations will provide template data sets designed to identify key PDR characteristics in JWST observations. These data will serve to benchmark PDR models and extend them into the JWST era. We also present the Science-Enabling products that we will provide to the community. These template data sets and Science-Enabling products will guide the preparation of future proposals on star-forming regions in our Galaxy and beyond and will facilitate data analysis and interpretation of forthcoming JWST observations., Support for JWST-ERS program ID 1288 was provided through grants from the STScI under NASA contract NAS5-03127 to STScI (K.G., D.V.D.P., M.R.), Univ. of Maryland (M.W., M.P.), Univ. of Michigan (E.B., F.A.), and Univ. of Toledo (T.S.-Y.L.). O.B. and E.H. are supported by the Programme National “Physique et Chimie du Milieu Interstellaire” (PCMI) of CNRS/INSU with INC/INP co-funded by CEA and CNES, and through APR grants 6315 and 6410 provided by CNES. E. P. and J.C. acknowledge support from the National Science and Engineering Council of Canada (NSERC) Discovery Grant program (RGPIN-2020-06434 and RGPIN-2021-04197 respectively). E.P. acknowledges support from a Western Strategic Support Accelerator Grant (ROLA ID 0000050636). J.R.G. and S.C. thank the Spanish MCINN for funding support under grant PID2019-106110GB-I00. Work by M.R. and Y.O. is carried out within the Collaborative Research Centre 956, subproject C1, funded by the Deutsche Forschungsgemeinschaft (DFG)—project ID 184018867. T.O. acknowledges support from JSPS Bilateral Program, grant No. 120219939. M.P. and M.W. acknowledge support from NASA Astrophysics Data Analysis Program award #80NSSC19K0573. C.B. is grateful for an appointment at NASA Ames Research Center through the San José State University Research Foundation (NNX17AJ88A) and acknowledges support from the Internal Scientist Funding Model (ISFM) Directed Work Package at NASA Ames titled: “Laboratory Astrophysics—The NASA Ames PAH IR Spectroscopic Database.”

Machine learning (ML) techniques discover knowledge from large amounts of data. Modeling in ML is becoming essential to software systems in practice. The accuracy and efficiency of ML models have been focused on ML research communities, while there is less attention on validating the qualities of ML models. Validating ML applications is a challenging and time-consuming process for developers since prediction accuracy heavily relies on generated models. ML applications are written by relatively more data-driven programming based on the black box of ML frameworks. All of the datasets and the ML application need to be individually investigated. Thus, the ML validation tasks take a lot of time and effort. To address this limitation, we present a novel quality validation technique that increases the reliability for ML models and applications, called MLVal. Our approach helps developers inspect the training data and the generated features for the ML model. A data validation technique is important and beneficial to software quality since the quality of the input data affects speed and accuracy for training and inference. Inspired by software debugging/validation for reproducing the potential reported bugs, MLVal takes as input an ML application and its training datasets to build the ML models, helping ML application developers easily reproduce and understand anomalies in the ML application. We have implemented an Eclipse plugin for MLVal that allows developers to validate the prediction behavior of their ML applications, the ML model, and the training data on the Eclipse IDE. In our evaluation, we used 23,500 documents in the bioengineering research domain. We assessed the ability of the MLVal validation technique to effectively help ML application developers: (1) investigate the connection between the produced features and the labels in the training model, and (2) detect errors early to secure the quality of models from better data. Our approach reduces the cost of engineering efforts to validate problems, improving data-centric workflows of the ML application development.

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To derive a clinical prediction rule of termination of resuscitation (TOR) for out-of-hospital cardiac arrest (OHCA) with pre-hospital defibrillation given.This was a retrospective multicenter cohort study performed in three emergency departments (EDs) of three regional hospitals from 1/1/2012 to 31/12/2018. Patients of OHCA aged ≥18 years old were included. Those with post-mortem changes, return of spontaneous circulation and receiving no resuscitation in EDs were excluded. A TOR rule was derived by logistic regression analysis based on demographics and end-tidal carbon dioxide level of included subjects with pre-hospital defibrillation given.There were 447 included patients had received pre-hospital defibrillation, in which 148 had return of spontaneous circulation (ROSC), with 22 survived to discharge (STD). Independent predictors for death on or before ED arrival (no ROSC) included EMS call to ED time 20 min and ETCO2 level 20 mmHg from first three sets. A 2-criteria rule predicting death on or before ED arrival by fulfilling both of the independent predictors had a specificity of 0.95 (95% CI 0.90-0.98) and positive predictive value (PPV) of 0.95 (95% CI 0.90-0.98), if 2nd set of ETCO2 was used. The positive likelihood ratio was 10.04 (95% CI 4.83-20.89).The 2-criteria TOR rule for OHCA patients with pre-hospital defibrillation had a high specificity and PPV for predicting death on or before ED arrival.

Full list of authors: De Marco, Orsola; Akashi, Muhammad; Akras, Stavros; Alcolea, Javier; Aleman, Isabel; Amram, Philippe; Balick, Bruce; De Beck, Elvire; Blackman, Eric G.; Boffin, Henri M. J.; Boumis, Panos; Bublitz, Jesse; Bucciarelli, Beatrice; Bujarrabal, Valentin; Cami, Jan; Chornay, Nicholas; Chu, You-Hua; Corradi, Romano L. M.; Frank, Adam; García-Hernández, D. A.; García-Rojas, Jorge; García-Segura, Guillermo; Gómez-Llanos, Veronica; Gonçalves, Denise R.; Guerrero, Martín A.; Jones, David; Karakas, Amanda I.; Kastner, Joel H.; Kwok, Sun; Lykou, Foteini; Manchado, Arturo; Matsuura, Mikako; McDonald, Iain; Miszalski, Brent; Mohamed, Shazrene S.; Monreal-Ibero, Ana; Monteiro, Hektor; Montez, Rodolfo; Baez, Paula Moraga; Morisset, Christophe; Nordhaus, Jason; Mendes de Oliveira, Claudia; Osborn, Zara; Otsuka, Masaaki; Parker, Quentin A.; Peeters, Els; Quint, Bruno C.; Quintana-Lacaci, Guillermo; Redman, Matt; Ruiter, Ashley J.; Sabin, Laurence; Sahai, Raghvendra; Contreras, Carmen Sánchez; Santander-García, Miguel; Seitenzahl, Ivo; Soker, Noam; Speck, Angela K.; Stanghellini, Letizia; Steffen, Wolfgang; Toalá, Jesús A.; Ueta, Toshiya; Van de Steene, Griet; Van Winckel, Hans; Ventura, Paolo; Villaver, Eva; Vlemmings, Wouter; Walsh, Jeremy R.; Wesson, Roger; Zijlstra, Albert A., Planetary nebulae—the ejected envelopes of red giant stars—provide us with a history of the last, mass-losing phases of 90% of stars initially more massive than the Sun. Here we analyse images of the planetary nebula NGC 3132 from the James Webb Space Telescope (JWST) Early Release Observations. A structured, extended hydrogen halo surrounding an ionized central bubble is imprinted with spiral structures, probably shaped by a low-mass companion orbiting the central star at about 40–60 au. The images also reveal a mid-infrared excess at the central star, interpreted as a dusty disk, which is indicative of an interaction with another closer companion. Including the previously known A-type visual companion, the progenitor of the NGC 3132 planetary nebula must have been at least a stellar quartet. The JWST images allow us to generate a model of the illumination, ionization and hydrodynamics of the molecular halo, demonstrating the power of JWST to investigate complex stellar outflows. Furthermore, new measurements of the A-type visual companion allow us to derive the value for the mass of the progenitor of a central star with excellent precision: 2.86 ± 0.06 M⊙. These results serve as pathfinders for future JWST observations of planetary nebulae, providing unique insight into fundamental astrophysical processes including colliding winds and binary star interactions, with implications for supernovae and gravitational-wave systems. © 2022, The Author(s), under exclusive licence to Springer Nature Limited., We acknowledge the International Astronomical Union that oversees the work of Commission H3 on Planetary Nebulae. It is through the coordinating activity of this committee that this paper came together. S.A. acknowledges support under the grant 5077 financed by IAASARS/NOA. J.A. and V.B. acknowledge support from the EVENTs/Nebulae-Web research programme, Spanish AEI grant PID2019-105203GB-C21. I.A. acknowledges the support of CAPES, Brazil (Finance Code 001). E.D.B. acknowledges financial support from the Swedish National Space Agency. E.G.B. acknowledges NSF grants AST-1813298 and PHY-2020249. J.C. and E.P. acknowledge support from an NSERC Discovery Grant. G.G.-S. thanks M. L. Norman and the Laboratory for Computational Astrophysics for the use of ZEUS-3D. D.A.G.-H. and A.M. acknowledge support from the ACIISI, Gobierno de Canarias and the European Regional Development Fund (ERDF) under grant with reference PROID2020010051 as well as from the State Research Agency (AEI) of the Spanish Ministry of Science and Innovation (MICINN) under grant PID2020-115758GB-I00. J.G.-R. acknowledges support from Spanish AEI under Severo Ochoa Centres of Excellence Programme 2020-2023 (CEX2019-000920-S). J.G.-R. and V.G.-L. acknowledge support from ACIISI and ERDF under grant ProID2021010074. D.R.G. acknowledges the CNPq grant 313016/2020-8. M.A.G. acknowledges support of grant PGC2018-102184-B-I00 of the Ministerio de Educación, Innovación y Universidades cofunded with FEDER funds and from the State Agency for Research of the Spanish MCIU through the ‘Center of Excellence Severo Ochoa’ award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). D.J. acknowledges support from the Erasmus+ programme of the European Union under grant number 2020-1-CZ01-KA203-078200. A.I.K. and Z.O. were supported by the Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013. This research is/was supported by an Australian Government Research Training Program (RTP) Scholarship. M.M. and R.W. acknowledge support from STFC Consolidated grant (2422911). C.M. acknowledges support from UNAM/DGAPA/PAPIIT under grant IN101220. S.S.M. acknowledges funding from UMiami, the South African National Research Foundation and the University of Cape Town VC2030 Future Leaders Award. J.N. acknowledges support from NSF grant AST-2009713. C.M.d.O. acknowledges funding from FAPESP through projects 2017/50277-0, 2019/11910-4 e 2019/26492-3 and CNPq, process number 309209/2019-6. J.H.K. and P.M.B. acknowledge support from NSF grant AST-2206033 and a NRAO Student Observing Support grant to Rochester Institute of Technology. M.O. was supported by JSPS Grants-in-Aid for Scientific Research(C) (JP19K03914 and 22K03675). Q.A.P. acknowledges support from the HKSAR Research grants council. Vera C. Rubin Observatory is a Federal project jointly funded by the National Science Foundation (NSF) and the Department of Energy (DOE) Office of Science, with early construction funding received from private donations through the LSST Corporation. The NSF-funded LSST (now Rubin Observatory) Project Office for construction was established as an operating centre under the management of the Association of Universities for Research in Astronomy (AURA). The DOE-funded effort to build the Rubin Observatory LSST Camera (LSSTCam) is managed by SLAC National Accelerator Laboratory (SLAC). A.J.R. was supported by the Australian Research Council through award number FT170100243. L.S. acknowledges support from PAPIIT UNAM grant IN110122. C.S.C.’s work is part of I+D+i project PID2019-105203GB-C22 funded by the Spanish MCIN/AEI/10.13039/501100011033. M.S.-G. acknowledges support by the Spanish Ministry of Science and Innovation (MICINN) through projects AxIN (grant AYA2016-78994-P) and EVENTs/Nebulae-Web (grant PID2019-105203GB-C21). R.S.’s contribution to the research described here was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. J.A.T. thanks the Marcos Moshisnky Fundation (Mexico) and UNAM PAPIIT project IA101622. E.V. acknowledges support from the ‘On the rocks II project’ funded by the Spanish Ministerio de Ciencia, Innovación y Universidades under grant PGC2018-101950-B-I00. A.A.Z. acknowledges support from STFC under grant ST/T000414/1. This research made use of Photutils, an Astropy package for detection and photometry of astronomical sources83, of the Spanish Virtual Observatory (https://svo.cab.inta-csic.es) project funded by MCIN/AEI/10.13039/501100011033/ through grant PID2020-112949GB-I00 and of the computing facilities available at the Laboratory of Computational Astrophysics of the Universidade Federal de Itajubá (LAC-UNIFEI, which is maintained with grants from CAPES, CNPq and FAPEMIG).

During the late asymptotic giant branch (AGB) phase of stellar evolution, the element carbon is created through the triple-α nuclear reaction. This is followed by the synthesis of other heavy elements via neutron capture in the core and the dredge-up of these elements to the surface by convection. Simple molecules and solid-state minerals begin to form in the upper photosphere. These molecules and solids are ejected into the interstellar medium by a strong stellar wind. During the subsequent post-AGB evolution, complex organics with aromatic and aliphatic structures are synthesized in the circumstellar envelope. Planetary nebulae, formed by swept-up circumstellar material, are found to show strong spectral signatures of ions, atoms, molecules, and inorganic and organic solids. These ejected materials of planetary nebulae serve as primordial ingredients of formation of new stars and planetary systems. Stellar synthesized organic solids may survive their journeys through the interstellar medium and evidence for remnants of such organics can be found in our own Solar System. In this paper, we summarize the recent observations of circumstellar synthesis of molecules and solids and discuss the implications of these ejected circumstellar materials on the chemical enrichment of the Galaxy and planetary systems.

The unidentified infrared (UIR) bands, whose carriers are thought to be organics, have been widely observed in various astrophysical environments. However, our knowledge of the detailed chemical composition and formation process of the carriers is still limited. We have synthesized laboratory organics named Quenched Nitrogen-included Carbonaceous Composite (QNCC) by quenching plasma produced from nitrogen gas and hydrocarbon solids. Infrared and X-ray analyses of QNCC showed that infrared properties of QNCC well reproduce the UIR bands observed in novae and amine structures contained in QNCC play an important role in the origin of the broad 8 m feature, which characterizes the UIR bands in novae. QNCC is at present the best laboratory analog of organic dust formed around dusty classical novae, which carries the UIR bands in novae via thermal emission process [Endo et al.(2021)].

Astronomical infrared spectral features at ∼6.6, 9.8 and 20 µm have recently been suggested as being due to the planar graphene form of C24 carbon cluster. Here, we report density functional theory...

A family of unidentified infrared emission (UIE) bands has been observed throughout the Universe. The current observed spectral properties of the UIE bands are summarized. These properties are discussed in the frameworks of different models of the chemical carriers of these bands. The UIE carriers represent a large reservoir of carbon in the Universe, and play a significant role in the physical and chemical processes in the interstellar medium and galactic environment. A correct identification of the carrier of the UIE bands is needed to use these bands as probes of galactic evolution.

A key yet unresolved question in modern-day astronomy is how galaxies formed and evolved under the paradigm of the $\Lambda$CDM model. A critical limiting factor lies in the lack of robust tools to describe the merger history through a statistical model. In this work, we employ a generative graph network, E(n) Equivariant Graph Normalizing Flows Model. We demonstrate that, by treating the progenitors as a graph, our model robustly recovers their distributions, including their masses, merging redshifts and pairwise distances at redshift z=2 conditioned on their z=0 properties. The generative nature of the model enables other downstream tasks, including likelihood-free inference, detecting anomalies and identifying subtle correlations of progenitor features., Comment: 6 pages, 3 figures, accepted to the ICML 2022 Machine Learning for Astrophysics workshop

Chemical kinetics plays an important role in governing the thermal evolution in reactive flows problems. The possible interactions between chemical species increase drastically with the number of species considered in the system. Various ways have been proposed before to simplify chemical networks with an aim to reduce the computational complexity of the chemical network. These techniques oftentimes require domain-knowledge experts to handcraftedly identify important reaction pathways and possible simplifications. Here, we propose a combination of autoencoder and neural ordinary differential equation to model the temporal evolution of chemical kinetics in a reduced subspace. We demonstrated that our model has achieved a close-to 10-fold speed-up compared to commonly used astro-chemistry solver for a 9-species primordial network, while maintaining 1 percent accuracy across a wide-range of density and temperature., Comment: 10 pages, 8 figures, accepted to the ICML 2022 Machine Learning for Astrophysics workshop

Although automated pathology classification using deep learning (DL) has proved to be predictively efficient, DL methods are found to be data and compute cost intensive. In this work, we aim to reduce DL training costs by pre-training a ResNet feature extractor using SimCLR contrastive loss for latent encoding of OCT images. We propose a novel active learning framework that identifies a minimal sub-sampled dataset containing the most uncertain OCT image samples using label propagation on the SimCLR latent encodings. The pre-trained ResNet model is then fine-tuned with the labelled minimal sub-sampled data and the underlying pathological sites are visually explained. Our framework identifies upto 2% of OCT images to be most uncertain that need prioritized specialist attention and that can fine-tune a ResNet model to achieve upto 97% classification accuracy. The proposed method can be extended to other medical images to minimize prediction costs.

There exists a number of astronomical spectral phenomena that have remained unidentified after decades of extensive observations. The diffuse interstellar bands, the 220 nm feature, unidentified infrared emission bands, extended red emissions, and 21 and 30 $\mu$m emission features are seen in a wide variety of astrophysical environments. The strengths of these features suggest that they originate from chemical compounds made of common elements, possibly organic in nature. The quest to understand how such organic materials are synthesized and distributed across the Galaxy represents a major challenge to our understanding of the chemical content of the Universe.

Web browsers have evolved into indispensable software platforms for modern applications. Although JavaScript has become a de-facto lingua franca for developing web applications, the JavaScript software development tools and methodologies lag behind those of languages such as Java and C#. In particular, to enhance JavaScript programs with non-functional concerns (e.g., persistence, security, transactions, and logging) JavaScript developers need to modify the source code by hand. Developers then often end up having to maintain the resulting modified version separately for reasons that include poor design, the complexities of program evolution, and fundamental language limitations. The necessity to modify code by hand could be avoided if JavaScript had metadata facilities for developers to specify non-functional concerns declaratively. To address this problem, we present a novel declarative approach, T ransparent A utomated E nhancement for J ava S cript (TAE-JS) that enhances JavaScript programs with the ability to use declarative metadata. The metadata is expressed by means of Java annotations. We have implemented our technique in an open-source plug-in for the Eclipse IDE. This plug-in allows a developer to enhance the original version of a JavaScript program by specifying concerns declaratively using Java annotations. It then analyzes an original version of the program to automatically generate enhanced program versions by adding the declared concerns. We evaluated TAE-JS with four practical examples that enhance JavaScript programs by declaratively adding concerns such as persistence, security, transactions, and logging. In a user study with ten student developers and three professional engineers at PayPal, the participants viewed favorably TAE-JS's flexible declarative enhancement capabilities, seeing them as a valuable mechanism for implementing non-functional concerns in JavaScript programs. Our evaluation results are promising in demonstrating the potential benefits of our approach to complement existing JavaScript development tools.

We present QUOTAS, a novel research platform for the data-driven investigation of super-massive black hole (SMBH) populations. While SMBH data sets -- observations and simulations -- have grown rapidly in complexity and abundance, our computational environments and analysis tools have not matured commensurately to exhaust opportunities for discovery. Motivated to explore BH host galaxy and the parent dark matter halo connection, in this pilot version of QUOTAS, we assemble and co-locate the high-redshift, luminous quasar population at $z \geq 3$ alongside simulated data of the same epochs. Leveraging machine learning algorithms (ML) we expand simulation volumes that successfully replicate halo populations beyond the training set. Training ML on the Illustris-TNG300 simulation that includes baryonic physics, we populate the larger LEGACY Expanse dark matter-only box with quasars. Our first science results comparing observational and ML simulated quasars at $z \sim 3$, reveal that while the recovered Black Hole Mass Functions and clustering are in good agreement, simulated SMBHs fail to accrete, shine and grow at high enough rates to match observed quasars. We conclude that sub-grid models of mass accretion and SMBH feedback implemented in Illustris-TNG300 do not reproduce their observed mass growth. QUOTAS, demonstrates the power of ML, both for analyzing large complex datasets, and offering a unique opportunity to interrogate our theoretical model assumptions. We deploy ML again to derive and devise an optimal survey strategy for bringing the undetected lower luminosity quasar population into view. QUOTAS, and all related materials are publicly available at the Google Kaggle platform., Revised version: 38 pages, 4 tables and 14 figures, accepted for publication in ApJ

Although automated pathology classification using deep learning (DL) has proved to be predictively efficient, DL methods are found to be data and compute cost intensive. In this work, we aim to reduce DL training costs by pre-training a Resnet feature extractor using SimCLR contrastive loss for latent encoding of OCT images. We propose a novel active learning framework that identifies a minimal sub-sampled dataset containing the most uncertain OCT image samples using label propagation on the SimCLR latent encodings. The pre-trained Resnet model is then fine-tuned with the labelled minimal sub-sampled data and the underlying pathological sites are visually explained. Our framework identifies upto 2% of OCT images to be most uncertain that need prioritized specialist attention and that can fine-tune a Resnet model to achieve upto 97% classification accuracy. The proposed method can be extended to other medical images to minimize prediction costs., 4 pages, 6 images, 2 tables, submitted to IEEE EMBC 2021

The Earth system consists of the physical components of land, oceans, atmosphere, and biosphere. The biosphere refers to the thin layer on the crust of the Earth where living organisms are found. The concept that the Earth is a self-contained system was first proposed by Russian geologist Vladimir Vernadsky (1863–1945) in his book Biosphere in 1926. This idea was revived 50 years later by English environmentalist James Lovelock (1919–), who proposed the Gaia hypothesis, which states that the Earth’s crust, the oceans, the atmosphere, and the biosphere are all part of a single entity. All these components are actively interacting with each other and changes in one component will lead to feedback in the other components. We now know that the early Earth acquired some water from its crust. After the emergence of life from this small pond, oxygen released from bacteria substantially increased the amount of oxygen in the atmosphere (Sect. 21.2). The subsequent evolution of life was affected by the changing physical conditions of the Earth.

As soon as humans developed a sense of awareness of their surroundings, they realized that their lives are governed by daily cycles of day and night and annual cycles of seasons. They also made the association that these cycles are related to the Sun. For practical and religious reasons, they became keen observers of the heavens. Our ancestors were in awe not only of the existence of celestial objects – the Sun, the Moon, and the stars – but also of the fact that they all move. Not only do they move, but they also do so in regular patterns. The Sun, the Moon, and the stars rise day after day without fail. After the Sun sets and the Earth is covered in darkness, stars can be seen to rise from the eastern horizon, move across the sky, and set in the opposite horizon. The existence of these repeated patterns was believed to be a sign of divine governance and a source of messages from the gods. Motivated by the desire to decipher the hidden meaning of these patterns, our ancestors observed the movement of celestial objects with great diligence.

The speculation that there could be extraterrestrial life began soon after Copernicus demoted the Earth to the status of just one of the planets. Galileo’s 1610 telescopic observation of the lunar surface led Kepler to suggest that the circular features seen on the Moon might be artificial constructions by lunar inhabitants. John Wilkins (1614–1672), Master of Trinity College, Cambridge and Bishop of Chester, wrote in his 1638 book The Discovery of a World in the Moon that the Moon may be inhabited by intelligent beings, and speculated on future journeys to the Moon and encounters with a lunar civilization. William Herschel was a firm believer in life on the Moon. In 1780, he wrote “… the almost absolute certainty, of her (the Moon) being inhabited” and observed features on the Moon were the “works of the lunarians and may be called their towns.” The idea that the Moon is populated by life remained popular well into the nineteenth century. An 1835 news report in the New York Sun, wrongly attributed to observations by John Herschel, reported the observation of forests, fields, beaches, and even winged creatures on the Moon. The Scottish astronomer Thomas Dick (1774–1857), in his 1838 book Celestial Scenery, estimated that there were over 22 trillion inhabitants on planets of the Solar System.

The question of the origin of life was probably asked as soon as humans developed self-consciousness. Our ancestors realized very early that plants, animals, and humans, are distinct from non-living entities on Earth such as rocks, water, and air. Where did life come from? The universally common explanation among early civilizations was supernatural intervention. Almost all early cultures and ancient civilizations believed that they owed their existence to a supreme being, who also created the Earth and other celestial bodies.

Much of the ancient knowledge of the world was derived from astronomical observations. By observing the shadow of the Earth during a lunar eclipse, Greek astronomers knew that the Earth was spherical in shape. By comparing the maximum altitudes of the Sun at noon on the longest day of the year (summer solstice) at Syene and Alexandria in Egypt and measuring the distance between Syene and Alexandria, Eratosthenes obtained a good estimate of the size of the Earth in the third century B.C. (Chap. 12, Vol. 1). By noting that the star Canopus could be observed just at the horizon at the island of Rhodes but rises to a maximum altitude of 1/48 of a full circle (7.5°) at Alexandria, Posidonius (135–51 B.C.) determined the circumference of the Earth by estimating the distance between these two locations. By the first century B.C., not only the spherical shape of the Earth was known, its size had also been measured to a reasonable degree of accuracy. Based on this knowledge, Greek geographer Strabo (64 B.C.–24 A.D.) wrote in his book Geography about the possibility of traveling to Asia by sailing west from Europe, 1500 years before Christopher Columbus.

The belief that there is a human–star connection can be traced back to antiquity. Among all the celestial objects, the Sun’s effect on human lives is the most evident. Light from the Sun allows humans to see our surroundings and to function during the day, and the Sun provides the warmth that keeps us alive. The annual movement of the Sun is the cause of the seasons, whose temperature variations dictate the living patterns of the human population. The position of the Sun in the zodiac constellations gives a reliable signal to farmers for when to plow, seed, harvest, and store their grains. It is not an accident that many ancient cultures worship the Sun god, because the Sun is the most important object in their lives.

Copernicus published his heliocentric theory in 1543, but acceptance was by no means immediate. His theory was not simpler than Ptolemy’s (Copernicus’s model has more epicycles) or more accurate, and it was contradictory to common sense. Copernicus replaced the hypothesis of the rotation of a celestial sphere with the hypothesis of a rotating Earth, and the apparent annual motion of the Sun by the Earth revolving around the Sun. Both of these hypotheses can be tested observationally. The lack of evidence for the Earth’s rotation and revolution was the reason most scholars were skeptical about the heliocentric theory.

In Aristotle’s cosmology, stars are eternal. By the nineteenth century, astronomers realized that stars can be sorted into different groups based on their spectral properties. The spectral classification of stars (Sect. 9.7) led to the idea that stars are born differently and evolve differently, leading to a paradigm shift from a static view to evolution. We now believe that stars do not live forever, and they have a life cycle of birth and death just like humans and animals. From the age of the Earth and the Solar System, we know that the Sun must be at least 4.6 billion years old, and it has been shining almost constantly at the present luminosity for much of this time. By comparing the present rate of nuclear fuel consumption and the expected total supply of fuel, one can estimate the lifetime of the Sun. Through the construction of models of the structure of the Sun and calculations of its rate of energy generation, astronomers estimate that the Sun will have a total lifetime of about 10 billion years. In other words, the Sun will have about another 5 billion years to live.

In traditional Greek philosophy, matter on Earth was composed of four basic elements: earth, air, fire, and water. For objects in the heavens, Aristotle declared “that there is something beyond the bodies that are about us on this earth, different and separate from them.” Heavenly objects were believed to be made of materials different from anything found on Earth. Aristotle named this ingredient of celestial objects “ether.”

Among all the living species, humans are the only ones who observe the world and ask questions about how and why. The ability to seek patterns from observations and formulate theories to explain and predict past and future events is the essence of science. In this book (and Volume 1), we have explained why astronomy is the oldest science. Recognizing that the celestial objects move with repeatable patterns, our ancestors developed quantitative models to describe these patterns. They were also motivated by the desire to seek possible connections between heaven, Earth, and humanity. The ancient discipline of astrology later became the discipline of astronomy, which systematically studies the positions, movements, brightness, and shapes of celestial objects. Astronomy further evolved into astrophysics, using our knowledge of terrestrial physics acquired in the laboratory to understand the structure of celestial objects. Spectroscopy made possible the identification of atoms and molecules in stars, interstellar space, and galaxies. These identifications suggest that the laws of physics and chemistry are applicable over large spatial scales across the Universe and back in time to billions of years ago.

One of the basic premises of Aristotle’s cosmological view is the distinction between heaven and Earth. Aristotle divided the cosmos into two regions. The first, the terrestrial world below the orbit of the Moon (sublunary), is unpredictable and constantly changing. The Earth has varying weather patterns and suffers from destructive hurricanes, volcanic eruptions, floods, and other unpredictable natural disasters. Above the orbit of the Moon, there is tranquility. The second, the superlunary world consisting of the Sun, planets, and the stars, is unchanging and everlasting. Not only are the contents of these worlds different, they are also governed by different laws of motion. Motions on Earth are either “violent motions” caused by physical contact, or “natural motions” of falling objects. Terrestrial motions have a beginning and an end. In contrast, motions of celestial objects are continuous and eternal: they move uniformly in trajectories of perfect circles.

In Aristotle’s view, celestial objects are simple, pure, and constant, in contrast to the terrestrial environment, which is dirty, complex, and variable. By the nineteenth century, we have learned that celestial objects are made of the same chemical elements as the Earth. These basic elements are in the form of atomic gases in stars. Stars are balls of gases held together by gravity. Galaxies are just assemblies of stars, which again are bound together by the force of gravity.

In the pre-telescope era, Ptolemy and Tycho Brahe listed approximately 1000 stars in their catalogs. The gradual improvements of telescopes have greatly increased the inventory of stars. In 1801, an extensive star catalog of 47,390 stars was compiled at the Paris Observatory. Between 1852 and 1859, the Bonn Observatory cataloged the positions and magnitudes of 320,000 stars. These catalogs were later supplemented by observations obtained in the southern hemisphere. The higher sensitivity that came with the invention of photographic plates in the nineteenth century also made the detection of stars much more efficient. In the 300-years period after Galileo’s first telescope astronomical observations, the known content of the Universe expanded from thousands to millions of stars.

Until the late eighteenth century, it was commonly believed that our world has been the same since the time of biblical Creation. By the nineteenth century, the view of a constant and everlasting Universe has become untenable and scientific opinion has shifted to a paradigm of change and evolution. The geological structure of the Earth is no longer viewed as static, but has undergone erosion, formation, and transformation. After Darwin, life is recognized as a process of nonstop evolution, with old species dying off and new species being created over the history of the Earth. This new perspective was driven by the study of biological fossils and layers of rock formation that gave scientists a record of how the Earth was at different times in the past.

Celestial objects in our Universe are not static. Much of the early history of astronomy was devoted to the study of motion of the Sun, the Moon, the stars, and the planets. Extensive observations were made to record their change in positions with time. The regular patterns of motions of celestial objects provided humans with the first impetus to understand the working of Nature.

For thousands of years, humans on Earth across all cultures knew of seven luminaries: The Sun; the Moon; and five planets, Mercury, Venus, Mars, Jupiter, and Saturn, all of which move relative to the fixed stars. The number seven was therefore considered special and sacred (Chap. 10, Vol. 1) and the possibility that there could be more than five planets had never entered anyone’s mind. After Copernicus proposed the heliocentric model, the Solar System was centered around the Sun, which had six planets (including the Earth) revolving around it. The Earth, therefore, became a part of the cosmic structure. Although the positions of the Solar System objects were re-arranged, the total number of celestial objects remained the same. When Galileo began his telescopic observations, he found that Jupiter has four moons similar to the Earth’s Moon (Chap. 20, Vol. 1). So, the Solar System consisted of a total of 11 objects: The Sun, six planets, and five moons. The special significance given to the number seven was therefore no longer secure.

In the previous chapters, we have outlined the journey of our realization of the expanding spatial size of the Universe. In this chapter, we will discuss how our concept of temporal history has also been expanding. Human history is based on generational oral and written accounting of events of the past. The oldest reliable written history is probably by the Chinese, who can trace written records back to the Shang Dynasty (~1500 B.C.). Earlier human history is mostly based on myths and legends. Nevertheless, we can safely assume that human civilization has been around for thousands of years.

The question of the nature of matter has a long history. Most ancient civilizations have pondered the question of the fundamental constituent of matter. Following the Greek philosophers Anaximander and Anaximenes, Aristotle proposed that terrestrial matter is made of four elements: earth, water, air and fire, and celestial bodies are made of ether. Elements were also linked to the concept of change. Heraclitus (535–575 B.C.) thought that it was natural for fire to go up and stone to fall down. The Chinese had a similar system of five fundamental elements (五行) that were left from the creation of the Universe: metal, wood, water, fire, and soil. According to the Taoist philosophy, these five elements not only makeup matter but also drive all natural processes. All terrestrial events, including functions in our body, are believed to be the result of transformations of these five elements. These five elements are also tied to celestial objects, with each corresponding to one of the five planets. The terrestrial–celestial integration forms the basis of Chinese astrology. The five elements, coupled with the concepts of yin (陰 related to the Moon, female) and yang (陽 related to the Sun, male), constitute the basis of the universal working of the Universe. Both the Greeks and the Chinese saw elements as constituents of matter as well as the cause of motion. The Chinese system is purely metaphysical and tries to be more encompassing than its Western counterpart.

After Copernicus removed the idea that the celestial sphere rotates around the Earth once a day, Thomas Digges suggested that there is no need for stars to all lie on the surface of the celestial sphere and an individual star can be at any distance from Earth. The Italian monk Giordano Bruno (1548–1600) raised the possibility that stars could be distant suns. In his book On the Infinite Universe and Worlds published in 1584, Bruno suggested that since there are planets revolving around the Sun, there could be planets (including other Earths) revolving around other stars. For these and other beliefs, Bruno was condemned to death for heresy in 1600 (Sect. 18.3, Vol. 1).

The first attempt to determine the size of the Solar System was by Ptolemy, who assumed that the Solar System was filled by the epicycles of the planets and there is no empty space in the Universe. From the sizes of the planetary epicycles need to fit the observed planetary orbits, he was able to estimate the size of the Solar System (Sect. 15.1, Vol. 1). In his book Planetary Hypothesis, Ptolemy listed the maximum distance of Saturn from Earth as 19,865 Earth radii, and this was used as the maximum extent of the Solar System. In the heliocentric model, Copernicus was able to determine the relative sizes of the planetary orbits (Sect. 16.2, Vol. 1). Because the physical sizes of the planetary orbits are scaled to the distance between the Earth and the Sun, this distance represents the key parameter for determining the size of the Solar System.

In Ptolemaic cosmology, the Universe has a finite size defined by the celestial sphere upon which the fixed stars lie. Within this celestial sphere are the five planets and the Sun revolving around the Earth. Assuming that the interior volume of the celestial sphere is filled by orbits and epicycles of the planets, Ptolemy derived a size of the Universe that is 20,000 times the radius of the Earth (Chap. 15, volume 1). After the development of the heliocentric theory, the hypothesis of the daily rotation of the celestial sphere was replaced by the hypothesis of the rotation of the Earth. This removes the need for the stars to lie at the same distance and rotate together, which in turn opens the possibility that the stars may have different distances from Earth and that the Universe could be infinite in size (Chap. 18, Vol. 1). While Copernicus replaced the Earth with the Sun as the center of the Universe, this cannot be true in an infinite Universe. An infinite Universe has no center, and therefore whether the Universe is finite or infinite has implications for our place in the Universe.

When Copernicus’s Six Books on the Revolutions of the Heavenly Spheres was published in 1543, he faced a number of theoretical objections to his theory. The hypotheses of rotation of the Earth and the Earth’s revolution around the Sun are central to the heliocentric theory but they are counter-intuitive. If the Earth is rotating eastward, then any object in the sky, such as flying birds and clouds, would be expected to drift in the opposite direction according to our common sense. In the sixteenth century, the understanding of the motion of objects was based on Aristotle’s distinction between “natural” and “violent” motions. If the rotation of the Earth is a natural motion (as it was interpreted by Copernicus) then a falling object would be left behind by the turning Earth. The fact that this is not observed was used as a strong argument against the rotation of the Earth.

Early civilizations relied on religion and mythology to explain the world that they lived in. The idea that celestial motions and the structure of the Universe are governed by natural processes that can be understood by rational thinking was pioneered by the Greeks. The first major figure to explore this concept was Thales of Miletus (625–545 B.C.). He was followed by his two disciples Anaximander (610–546 B.C.) and Anaximenes (585–528 B.C.). From observations of the apparent daily horizon-to-horizon trajectories of the Sun and the stars, Anaximander hypothesized that the Sun and stars move in complete circles, and they continue to move beneath the Earth even when they can no longer be seen. He, therefore, deduced that the Earth must be a free-floating, isolated object in space (Sect. 4.3, Vol. 1). This process of observations, summary of patterns, formulation of a hypothesis, and prediction of a new conclusion, formed the basis of the scientific way of thinking.

As the world wide web grows rapidly, a text corpus is becoming increased online at an incredible rate. Managing a corpus of documents is critical for many areas of science, industry, and culture. For example, bioengineering researchers, who study a new generation of advanced materials, frequently need to identify and understand a comprehensive body of literature describing an association between material features of interest. However, there is no inspection technique to help such researchers who need to make critical decisions based on their understanding of a corpus of documents. In this paper, we present a text visualization approach, TOPEXPLORER which extracts and visualizes topic models regarding bioengineering document collections. TOPEXPLORER displays text data in a logical layout to inspect and understand the relations among documents. It applies three probabilistic topic modeling algorithms as complementary study methods to systematically discover hidden thematic structures in a collection of documents. In the evaluation, we assessed TOPEXPLORER by building topic models on 600 documents in the bioengineering domain. The interactive visualization of TOPEXPLORER allows users to explore the hidden structure that a topic model discovers. TOPEXPLORER helps users understand and explore the output of models by effectively organizing, summarizing, visualizing, and interacting with a corpus.

Developers often make recurring changes, similar but different changes across multiple locations. They inspect such code changes per source file (i.e., a diff patch) during code reviews; however, diff patches represent low-level code modification without summarizing recurring changes, leading to tedious and error-prone code inspection. To address this problem, we propose a novel code review approach, Recurring Code Changes Inspection with Deep Learning (RIDL) that leverages change patterns of an edit script by learning code clones, identical or nearly similar code fragments. To train a classifier, RIDL learns 13,940 clones with four different clone types (e.g., Type-1, Type-2, Type-3, and Type-4 clones) from a clone database mined from 25,000 subject programs. Our approach then leverages the classifier to (1) interactively summarize recurring changes and (2) detect change mistakes, potential anomalies in a given codebase. In the evaluation, after 2 hours of training, RIDL analyzes code changes in four open source projects. It summarizes recurring changes with 95.1% accuracy and detects change anomalies with 93.1% accuracy. Our results show that RIDL should help developers effectively inspect recurring changes during code reviews.

Similar changes are common during the development of a project. Many of the changes are similar but appears different based on the local context. During code review the code changes are inspected per each source file. The process of identifying similar code change is time-taking and error-prone. To overcome this problem, we propose Similar Changes Inspection with Deep Learning (SIL) which (1) creates a generalized edit script based on the data and control dependence to (2) identify and summarize similar code changes by (3) modelling a deep learning classifier. In order to train a classifier, we have identified clones of four types from a clone database mined from 25,000 programs. SIL summarizes the changes and identifies the change anomalies. To obtain feedback on the SIL approach, we have conducted an user study with seven Computer Science students. The study revealed that SIL helped these developers to conduct peer code reviews more effectively. SIL is available as an Eclipse plug-in and its demonstration video is available at https://sites.google.com/unomaha.edu/codereview-deeplearning.

We report an unbiased radio line survey towards the circumstellar envelopes of evolved stars at the frequency range from 20 to 25 GHz, aiming to obtain a more complete unbiased picture of the chemical evolution in the final stages of stellar evolution. The observation sample includes the asymptotic giant branch (AGB) star IRC+10216, the proto-planetary nebulae (PPNs) CRL\,2688 and CRL\,618, and the young planetary nebula (PN) NGC\,7027, representing an evolutionary sequence spanning about 10,000 years. Rotational transitions from cyanopolyyne chains and inversion lines from ammonia are detected in the AGB star and PPNs, while the PN displays several recombination lines. The different spectral behaviors of these evolved stars clearly reflect the evolution of circumstellar chemistry during the AGB-PPN-PN transitions., 37 pages. 8 figures, Accepted for publication in PASJ

Astronomical infrared spectral features at ~6.6, 9.8 and 20 micronm have recently been suggested as being due to the planar graphene form of C24 carbon cluster. Here we report density functional theory and coupled cluster calculations on wavefunctions stability, relative energies, and infrared spectra of four different types of C24 isomers, including the graphene and fullerene forms. The types of vibrational motions under these bands are also discussed. Among the four isomers, we find that the astronomical data are best approximated by the graphene form of C24., 15 pages, 4 figures

We present high-angular-resolution {\it Hubble Space Telescope (HST)} optical and near-infrared imaging of the compact planetary nebula (PN) IRAS 21282+5050. Optical images of this object reveal several complex morphological structures including three pairs of bipolar lobes and an elliptical shell lying close to the plane of the sky. From near-infrared observations, we found a dust torus oriented nearly perpendicular to the major axis of elliptical shell. The results suggest that IRAS 21282+5050 is a multipolar PN, and these structures developed early during the post asymptotic-giant-branch (AGB) evolution. From a three-dimensional (3-D) model, we derived the physical dimensions of these apparent structures. When the 3-D model is viewed from different orientations, IRAS 21282+5050 shows similar apparent structures as other multipolar PNs. Analysis of the spectral energy distribution and optical spectroscopic observations of the nebula suggests the presence of a cool companion to the hot central star responsible for the ionization of the nebula. Whether the binary nature of the central star has any relations with the multipolar structure of the nebula needs to be further investigated.