86 research outputs found
21-cm absorption from galaxies at z ~ 0.3
We report the detection of 21-cm absorption from foreground galaxies towards
quasars, specifically z_gal = 0.3120 towards SDSS J084957.97+510829.0 (z_qso =
0.584; Pair-I) and z_gal = 0.3714 towards SDSS J144304.53+021419.3 (z_qso =
1.82; Pair-II). In both the cases, the integrated 21-cm optical depth is
consistent with the absorbing gas being a damped Lyman-\alpha (DLA) system. In
the case of Pair-I, strong Na I and Ca II absorption are also detected at z_gal
in the QSO spectrum. We identify an early-type galaxy at an impact parameter of
b ~ 14 kpc whose photometric redshift is consistent with that of the detected
metal and 21-cm absorption lines. This would be the first example of an
early-type galaxy associated with an intervening 21-cm absorber. The gas
detected in 21-cm and metal absorption lines in the outskirts of this luminous
red galaxy could be associated with the reservoir of cold H I gas with a low
level of star formation activity in the outer regions of the galaxy as reported
in the literature for z ~ 0.1 early-type galaxies. In the case of Pair-II, the
absorption is associated with a low surface brightness galaxy that, unlike most
other known quasar-galaxy pairs (QGPs) i.e. QSO sight lines passing through
disks/halos of foreground galaxies, is identified only via narrow optical
emission lines detected on top of the QSO spectra. Using SDSS spectra we infer
that the emission lines originate within ~ 5 kpc of the QSO sight line, and the
gas has metallicity [12+O/H] ~ 8.4 and star formation rate ~ 0.7-0.8 M_sun per
yr. The measured 21-cm optical depth can be reconciled with the N(H I) we
derive from the measured extinction (A_V=0.6) if either the H I gas is warm or
the extinction per hydrogen atom in this galaxy is much higher than the mean
value of the Small Magellanic Cloud. (Abridged)Comment: 8 pages, 7 figures, 3 tables (A&A in press
Penormaan Pengawasan Izin Lingkungan dalam Pencegahan Pencemaran dan Kerusakan Lingkungan Hidup dalam Eksploitasi Sumber Daya Alam
In environmental protection and management, the main effort is to prevent pollution and damage on environment instead of repressing the damages occurred. Permit is one of preventive measures and becomes a principle in Administrative Law. Permits can be seen as government\u27s tool as judicial preventive and used as an administrative instrument to control people\u27s behavior. Environmental permit can be seen as preventive measure, because it always related to orders and obligations that must be obeyed by the holder. On the other hand, environmental permit also function as repressive instrument to counter environmental problems due to human activities, including mining. The norm\u27s obscurity on the supervision of environmental permits in in Law No. 32 Year 2009 on Environmental Protection and Management (hereafter will refer as UUPPLH) is an indicator for the lack of the objective results.Based on type, this research focuses the study on the Environmental permit as an absolute requirement. Normatively, the principle of environmental permit as stipulated in Environmental Law regulates that every business and/or activity which required an Environmental Impact Analysis document or UKL-UPL should also hold an environmental permit. The purpose of Environmental permits is to maintain the preservation of environmental functions while also prevent and counter environmental pollution and damage due to human activities. Based on this construction, permits plays a very important role in environmental activity. Exploitation of natural resources has a significant impact on the environment, thus based on Article 22 paragraph (1) of Environmental Law these activities requires an Environment Impact Analysis. Important impacts as detailed in Article 22 paragraph (2) at empirical level still occurs so the goal of preventing pollution and damage as the objective of environmental permits still has not been achieved
A Zero-Positive Learning Approach for Diagnosing Software Performance Regressions
The field of machine programming (MP), the automation of the development of software, is making notable research advances. This is, in part, due to the emergence of a wide range of novel techniques in machine learning. In this paper, we apply MP to the automation of software performance regression testing. A performance regression is a software performance degradation caused by a code change. We present AutoPerf–a novel approach to automate regression testing that utilizes three core techniques:(i) zero-positive learning,(ii) autoencoders, and (iii) hardware telemetry. We demonstrate AutoPerf’s generality and efficacy against 3 types of performance regressions across 10 real performance bugs in 7 benchmark and open-source programs. On average, AutoPerf exhibits 4% profiling overhead and accurately diagnoses more performance bugs than prior state-of-the-art approaches. Thus far, AutoPerf has produced no false negatives
Learning Fitness Functions for Machine Programming
The problem of automatic software generation is known as Machine Programming.
In this work, we propose a framework based on genetic algorithms to solve this
problem. Although genetic algorithms have been used successfully for many
problems, one criticism is that hand-crafting its fitness function, the test
that aims to effectively guide its evolution, can be notably challenging. Our
framework presents a novel approach to learn the fitness function using neural
networks to predict values of ideal fitness functions. We also augment the
evolutionary process with a minimally intrusive search heuristic. This
heuristic improves the framework's ability to discover correct programs from
ones that are approximately correct and does so with negligible computational
overhead. We compare our approach with several state-of-the-art program
synthesis methods and demonstrate that it finds more correct programs with
fewer candidate program generations
An HST/COS legacy survey of high-velocity ultraviolet absorption in the Milky Way's circumgalactic medium and the Local Group
To characterize the absorption properties of this circumgalactic medium (CGM)
and its relation to the LG we present the so-far largest survey of metal
absorption in Galactic high-velocity clouds (HVCs) using archival ultraviolet
(UV) spectra of extragalactic background sources. The UV data are obtained with
the Cosmic Origins Spectrograph (COS) onboard the Hubble Space Telescope (HST)
and are supplemented by 21 cm radio observations of neutral hydrogen. Along 270
sightlines we measure metal absorption in the lines of SiII, SiIII, CII, and
CIV and associated HI 21 cm emission in HVCs in the velocity range
|v_LSR|=100-500 km s^-1. With this unprecedented large HVC sample we were able
to improve the statistics on HVC covering fractions, ionization conditions,
small-scale structure, CGM mass, and inflow rate. For the first time, we
determine robustly the angular two point correlation function of the
high-velocity absorbers, systematically analyze antipodal sightlines on the
celestial sphere, and compare the absorption characteristics with that of
Damped Lyman alpha absorbers (DLAs) and constrained cosmological simulations of
the LG. Our study demonstrates that the Milky Way CGM contains sufficient
gaseous material to maintain the Galactic star-formation rate at its current
level. We show that the CGM is composed of discrete gaseous structures that
exhibit a large-scale kinematics together with small-scale variations in
physical conditions. The Magellanic Stream clearly dominates both the cross
section and mass flow of high-velocity gas in the Milky Way's CGM. The possible
presence of high-velocity LG gas underlines the important role of the local
cosmological environment in the large-scale gas-circulation processes in and
around the Milky Way (abridged).Comment: 37 pages, 25 figures, 8 tables, accepted for publication in A&
The Relation Between Galaxy ISM and Circumgalactic OVI Gas Kinematics Derived from Observations and CDM Simulations
We present the first galaxy-OVI absorption kinematic study for 20 absorption
systems (EW>0.1~{\AA}) associated with isolated galaxies (0.150.55) that
have accurate redshifts and rotation curves obtained using Keck/ESI. Our sample
is split into two azimuthal angle bins: major axis () and
minor axis (). OVI absorption along the galaxy major axis is
not correlated with galaxy rotation kinematics, with only 1/10 systems that
could be explained with rotation/accretion models. This is in contrast to
co-rotation commonly observed for MgII absorption. OVI along the minor axis
could be modeled by accelerating outflows but only for small opening angles,
while the majority of the OVI is decelerating. Along both axes, stacked OVI
profiles reside at the galaxy systemic velocity with the absorption kinematics
spanning the entire dynamical range of their galaxies. The OVI found in AMR
cosmological simulations exists within filaments and in halos of ~50 kpc
surrounding galaxies. Simulations show that major axis OVI gas inflows along
filaments and decelerates as it approaches the galaxy while increasing in its
level of co-rotation. Minor axis outflows in the simulations are effective
within 50-75 kpc beyond that they decelerate and fall back onto the galaxy.
Although the simulations show clear OVI kinematic signatures they are not
directly comparable to observations. When we compare kinematic signatures
integrated through the entire simulated galaxy halo we find that these
signatures are washed out due to full velocity distribution of OVI throughout
the halo. We conclude that OVI alone does not serve as a useful kinematic
indicator of gas accretion, outflows or star-formation and likely best probes
the halo virial temperature.Comment: 24 pages, 21 figures, 4 tables. Accepted to ApJ on November 14, 201
Large Language Models Based Automatic Synthesis of Software Specifications
Software configurations play a crucial role in determining the behavior of
software systems. In order to ensure safe and error-free operation, it is
necessary to identify the correct configuration, along with their valid bounds
and rules, which are commonly referred to as software specifications. As
software systems grow in complexity and scale, the number of configurations and
associated specifications required to ensure the correct operation can become
large and prohibitively difficult to manipulate manually. Due to the fast pace
of software development, it is often the case that correct software
specifications are not thoroughly checked or validated within the software
itself. Rather, they are frequently discussed and documented in a variety of
external sources, including software manuals, code comments, and online
discussion forums. Therefore, it is hard for the system administrator to know
the correct specifications of configurations due to the lack of clarity,
organization, and a centralized unified source to look at. To address this
challenge, we propose SpecSyn a framework that leverages a state-of-the-art
large language model to automatically synthesize software specifications from
natural language sources. Our approach formulates software specification
synthesis as a sequence-to-sequence learning problem and investigates the
extraction of specifications from large contextual texts. This is the first
work that uses a large language model for end-to-end specification synthesis
from natural language texts. Empirical results demonstrate that our system
outperforms prior the state-of-the-art specification synthesis tool by 21% in
terms of F1 score and can find specifications from single as well as multiple
sentences
A Study of User Activity Patterns and the Effect of Venue Types on City Dynamics Using Location-Based Social Network Data
The main purpose of this research is to study the effect of various types of venues on the density distribution of residents and model check-in data from a Location-Based Social Network for the city of Shanghai, China by using combination of multiple temporal, spatial and visualization techniques by classifying users’ check-ins into different venue categories. This article investigates the use of Weibo for big data analysis and its efficiency in various categories instead of manually collected datasets, by exploring the relation between time, frequency, place and category of check-in based on location characteristics and their contributions. The data used in this research was acquired from a famous Chinese microblogs called Weibo, which was preprocessed to get the most significant and relevant attributes for the current study and transformed into Geographical Information Systems format, analyzed and, finally, presented with the help of graphs, tables and heat maps. The Kernel Density Estimation was used for spatial analysis. The venue categorization was based on nature of the physical locations within the city by comparing the name of venue extracted from Weibo dataset with the function such as education for schools or shopping for malls and so on. The results of usage patterns from hours to days, venue categories and frequency distribution into these categories as well as the density of check-in within the Shanghai and contribution of each venue category in its diversity are thoroughly demonstrated, uncovering interesting spatio-temporal patterns including frequency and density of users from different venues at different time intervals, and significance of using geo-data from Weibo to study human behavior in variety of studies like education, tourism and city dynamics based on location-based social networks. Our findings uncover various aspects of activity patterns in human behavior, the significance of venue classes and its effects in Shanghai, which can be applied in pattern analysis, recommendation systems and other interactive applications for these classes.</jats:p
Detection of two intervening Ne viii absorbers probing warm gas at z ~ 0.6
Large scale structure and cosmolog
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