bluuebunny/crossref_metadata_2025_split huggingface dataset:
After The Fall: Resolving the Molecular Gas in Post-starburst Galaxies
Authors: Smercina Adam , Smith John-David T. , French K. Decker , Bell Eric F. , Dale Daniel A. , Medling Anne M. , Nyland Kristina , Privon George C. , Rowlands Kate , Walter Fabian , Zabludoff Ann I. 
Published: April 2022

Abstract
Post-starburst (PSB), or “E + A,” galaxies represent a rapid transitional phase between major, gas-rich mergers and gas-poor, quiescent, early-type galaxies. Surprisingly, many PSBs have been shown to host a significant interstellar medium (ISM), despite theoretical predictions that the majority of the star-forming gas should be expelled in active galactic nuclei– or starburst-driven outflows. To date, the resolved properties of this surviving ISM have remained unknown. We present high-resolution ALMA continuum and CO(2–1) observations in six gas- and dust-rich PSBs, revealing for the first time the spatial and kinematic structure of their ISM on sub-kpc scales. We find extremely compact molecular reservoirs, with dust and gas surface densities rivaling those found in (ultra)luminous infrared galaxies. We observe spatial and kinematic disturbances in all sources, with some also displaying disk-like kinematics. Estimates of the internal turbulent pressure in the gas exceed those of normal star-forming disks by at least 2 orders of magnitude, and rival the turbulent gas found in local interacting galaxies, such as the Antennae. Though the source of this high turbulent pressure remains uncertain, we suggest that the high incidence of tidal disruption events in PSBs could play a role. The star formation in these PSBs’ turbulent central molecular reservoirs is suppressed, forming stars only 10% as efficiently as starburst galaxies with similar gas surface densities. “The fall” of star formation in these galaxies was not precipitated by complete gas expulsion or redistribution. Rather, this high-resolution view of PSBs’ ISM indicates that star formation in their remaining compact gas reservoirs is suppressed by significant turbulent heating.
Cloud-convection Feedback in Brown Dwarf Atmospheres
Authors: Lefèvre Maxence , Tan Xianyu , Lee Elspeth K. H. , Pierrehumbert R. T. 
Published: April 2022

Abstract
Numerous observational evidence has suggested the presence of active meteorology in the atmospheres of brown dwarfs. A near-infrared brightness variability has been observed. Clouds have a major role in shaping the thermal structure and spectral properties of these atmospheres. The mechanism of such variability is still unclear, and neither 1D nor global circulation models can fully study this topic due to resolution. In this study, a convective-resolving model is coupled to gray-band radiative transfer in order to study the coupling between the convective atmosphere and the variability of clouds over a large temperature range with a domain of several hundred kilometers. Six types of clouds are considered, with microphysics including settling. The clouds are radiatively active through the Rosseland mean coefficient. Radiative cloud feedback can drive spontaneous atmospheric variability in both temperature and cloud structure, as modeled for the first time in three dimensions. Silicate clouds have the most effect on the thermal structure with the generation of a secondary convective layer in some cases, depending on the assumed particle size. Iron and aluminum clouds also have a substantial impact on the atmosphere. Thermal spectra were computed, and we find the strongest effect of the clouds is the smoothing of spectral features at optical wavelengths. Compared to observed L and T dwarfs on the color–magnitude diagram, the simulated atmospheres are redder for most of the cases. Simulations with the presence of cloud holes are closer to observations.
Damped Lyα Absorbers in Star-forming Galaxies at z < 0.15 Detected with the Hubble Space Telescope and Implications for Galactic Evolution
Authors: Kulkarni Varsha P. , Bowen David V. , Straka Lorrie A. , York Donald G. , Gupta Neeraj , Noterdaeme Pasquier , Srianand Raghunathan 
Published: April 2022

Abstract
We report Hubble Space Telescope Cosmic Origins Spectrograph spectroscopy of 10 quasars with foreground star-forming galaxies at 0.02 < z < 0.14 within impact parameters of ∼1–7 kpc. We detect damped/sub-damped Lyα (DLA/sub-DLA) absorption in 100% of cases where no higher-redshift Lyman-limit systems extinguish the flux at the expected wavelength of Lyα absorption, obtaining the largest targeted sample of DLA/sub-DLAs in low-redshift galaxies. We present absorption measurements of neutral hydrogen and metals. Additionally, we present Green Bank Telescope 21 cm emission measurements for five of the galaxies (including two detections). Combining our sample with the literature, we construct a sample of 117 galaxies associated with DLA/sub-DLAs spanning 0 < z < 4.4, and examine trends between gas and stellar properties, and with redshift. The H i column density is anticorrelated with impact parameter and stellar mass. More massive galaxies appear to have gas-rich regions out to larger distances. The specific star formation rate (sSFR) of absorbing galaxies increases with redshift and decreases with M*, consistent with evolution of the star formation main sequence (SFMS). However, ∼20% of absorbing galaxies lie below the SFMS, indicating that some DLA/sub-DLAs trace galaxies with longer-than-typical gas-depletion timescales. Most DLA/sub-DLA galaxies with 21 cm emission have higher H i masses than typical galaxies with comparable M*. High M
HI/M* ratios and high sSFRs in DLA/sub-DLA galaxies with M* < 109
M
⊙ suggest these galaxies may be gas-rich because of recent gas accretion rather than inefficient star formation. Our study demonstrates the power of absorption and emission studies of DLA/sub-DLA galaxies for extending galactic evolution studies to previously under-explored regimes of low M* and low SFR.
Accurate Machine-learning Atmospheric Retrieval via a Neural-network Surrogate Model for Radiative Transfer
Authors: Himes Michael D. , Harrington Joseph , Cobb Adam D. , Güneş Baydin Atılım , Soboczenski Frank , O’Beirne Molly D. , Zorzan Simone , Wright David C. , Scheffer Zacchaeus , Domagal-Goldman Shawn D. , Arney Giada N. 
Published: April 2022

Abstract
Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratios of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each model parameter, given observed spectra. This inference is computationally expensive, as it requires many executions of a costly radiative transfer (RT) simulation for each set of sampled model parameters. Machine learning (ML) has recently been shown to provide a significant reduction in runtime for retrievals, mainly by training inverse ML models that predict parameter distributions, given observed spectra, albeit with reduced posterior accuracy. Here we present a novel approach to retrieval by training a forward ML surrogate model that predicts spectra given model parameters, providing a fast approximate RT simulation that can be used in a conventional Bayesian retrieval framework without significant loss of accuracy. We demonstrate our method on the emission spectrum of HD 189733 b and find good agreement with a traditional retrieval from the Bayesian Atmospheric Radiative Transfer (BART) code (Bhattacharyya coefficients of 0.9843–0.9972, with a mean of 0.9925, between 1D marginalized posteriors). This accuracy comes while still offering significant speed enhancements over traditional RT, albeit not as much as ML methods with lower posterior accuracy. Our method is ∼9× faster per parallel chain than BART when run on an AMD EPYC 7402P central processing unit (CPU). Neural-network computation using an NVIDIA Titan Xp graphics processing unit is 90×–180× faster per chain than BART on that CPU.
Improving Glycemic Control With the Adjunct Use of a Data Management Software Program
Authors: Reed Charles C. , Richa Jacqueline M. , Berndt Andrea E. , Beadle Randy D. , Gerhardt Susan D. , Stewart Ronald , Corneille Michael 
Published: April 2022

Background
Published studies have supported the implementation of tight glucose control (TGC) programs to improve patient outcomes and reduce mortality rates. However, measuring a program’s efficiency is challenging, because of a lack of systems that capture data, allow access to data, and support analysis and interpretation in a near prospective time frame. We hypothesized that providing clinicians access to real-time blood glucose (BG) results reports could improve the efficacy of our TGC program.

Methods
We performed a retrospective review of BG data during a 12-month period in a surgical trauma intensive care unit at a level I trauma center. A unit-specific insulin algorithm was used throughout the study. We compared BG values before and after the implementation of a data management software program that allowed clinicians access to real-time BG results reports. Reports were run daily and weekly to monitor the unit’s TGC program.

Results
A total of 70 616 BG values from 1044 patients were analyzed. An overall decrease was observed in the BG level mean, from 121 mg/ dL to 112 mg/dL (P&lt;.001), as well as a decrease in the aggregated mean across patients, from 132 mg/dL to 119 mg/dL (P&lt;.001), after implementation of the software. The percentage of values within the target range of 80 to 110 mg/dL increased from 38.9% to 50.4% (P&lt;.001). The percentage of BG values less than 70 increased from 2.7% to 3.4% (P&lt;.001). However, the percentage of severe hypoglyce-mic episodes (≤40 mg/dL) remained unchanged.

Conclusions
Access to real-time aggregated BG data reports through the use of a data management software program improved the efficacy of our TGC program.
Energy Transition Meets Digital Transformation: Design and Implementation of a Comprehensive Carbon Emissions Estimation and Forecasting Platform
Authors: Rafiee Javad , Sarma Pallav , Gutierrez Fernando , Hilliard Ryan , Calad Carlos Mario , Angulo Oscar , Boyer Brian 
Published: April 2022

Abstract
With growing worldwide consensus about the impacts of climate change, the oil and gas industry faces unprecedented pressure to redefine itself, minimize its carbon footprint, and ultimately move towards net zero emissions. It is therefore imperative that the industry can easily and accurately measure its carbon footprint, forecast impact on emissions from operational decisions, monitor key sources of emissions and ultimately minimize it via operational and other optimizations. This need is further accelerated by regulatory, investor, consumer, and market forces, in many cases making it mandatory for corporations to report their carbon footprints. The objective of this work is to present the design and implementation of a carbon estimation and forecasting platform, henceforth called Aurion, to be the one-stop-shop for all the carbon needs of the oil and gas industry.
We leverage the Environmental Protection Agency (EPA) Subpart W model and the California Air Resources Board (CARB) OPGEE model as the underlying calculation engines for estimating carbon intensity and footprint. Subpart W is an equipment and inventory-based accounting approach to estimating carbon footprint, and is mandated by EPA for the oil and gas industry for all operations that emit more than 25000 MT of CO2 equivalent. OPGEE is a life-cycle assessment (LCA) tool that estimates the GHG emissions of petroleum production operations from reservoir to transport to the refinery. Using these well-known tools not only provides a robust, tested, and reliable approach to estimate carbon intensity, but also provides standardization and transparency to all calculations, thereby making it thoroughly auditable and consistent across an organization.
Aurion provides a user-friendly, cloud based, scalable interface to Subpart W and OPGEE, and allows users to seamlessly integrate various sources of data (public, private, third party) for continuous estimation and monitoring of GHG emissions across the whole organization. It further integrates with production forecasts to provide an estimate for future carbon footprint and intensity to understand the GHG impact of different operational plans. Additionally, the platform provides tools for collaboration, as estimating carbon intensity requires expertise and data from many domains. Sensitivity analysis is also implemented to understand key factors impacting carbon intensity for a field and helps the managers to make sustainable decisions and reduce their carbon footprint. Aurion also provides standard ESG frameworks and customizable surveys for understanding and documenting additional GHG emissions related issues. Finally, Aurion provides tools to aggregate, report and benchmark GHG emissions across an organization.
The Use of Localized Well-Drainage Reservoir Pressure Model in Fracturing Design and Optimization
Authors: Ekeregbe Merit P. 
Published: April 2022

Abstract
This study is to determine the effective use of localized reservoir pressure of each well drainage area in a multi-well reservoir system model to determine optimum fracturing design for production improvement.
A static bottom-hole pressure (BHP) survey may present different values for each well draining from the same reservoir but these different pressure values have not been incorporated into determining the performance of each individual well based on the pressure as seen by each well, rather an indeterminate average reservoir pressure is used. Fracturing as a concept of increasing reservoir permeability will further expose the well to reservoir pressure as seen by the individual well than the assumed single-value reservoir-wide pressure. This is so except when the fracture half-length is equal to the drainage length of the reservoir, connecting the whole reservoir to justify the single reservoir pressure effect if it is a single-well reservoir system. In reality, many reservoirs are multi-well reservoir systems and this simplified assumption may pose some drawbacks. The damaged wellbore area may truly be more exposed to the localized reservoir pressure as seen by the well than the apparent reservoir single value pressure assumed to determine drawdown and damage. In a multi-well reservoir system with each well-drainage area subjected to different reservoir pressures than the single reservoir pressure, fracturing and stimulation candidates screening may not present the actual effect of each well-drainage area static reservoir pressure.
This paper is to present a new model that incorporates the average reservoir pressure for whole reservoir system and the reservoir pressure as seen by individual wells in the determination of the drawdown and damage. The knowledge of the different pressures in different well locations in the reservoir system will be utilized to present a linear flow model in well fracturing to enhance better well performance.
With this new model, the actual and more realistic damage estimation and ways to achieve a linear flow for optimum performance through fracturing will be better understood. The effect of other flowing wells on the skin of the candidate well will enhance a better planning than is done now because the existing formulations are done with a single-well reservoir system in mind; no account for contributing skin of other flowing wells in the industry applied model approaches.
Offshore Liquefied Natural Gas LNG and Monetization
Authors: Alabi Femi Adeoye 
Published: April 2022

Abstract

Objectives/Scope
The development of gas market has been allowed to evolve with the introduction of the GMP (Gas Master Plan). A well-thought process plan of gas infrastructural development model that supports flexible growth of the local market, consolidation of strategic export and regional market expansion. The lock-in areas are expressly re-navigated for easy processing and gas transportation. This paper would contain a detailed striking difference between LNG and international pipeline gas business for all regions.

Methods, Procedures, Process
The GMP elements are created to assist or support the intentions of the government in solidifying the economy and policy formulation that entails natural gas pricing to tackle the long term price model problem. The hinterland gas networking and monetization and its untapped wealth should be evaluated and explored. FLNG can change the oil and gas business from a business and technical viewpoint by influencing the economic development of inaccessible offshore oil and gas fields.

Results, Observations, Conclusions
This section unveils the investment opportunity involved in GMP. By critically analyzing the GMP, it will reveal certain lapses like lack of proper regulatory, legal and policy framework, which are major challenges in the achievements of GMP aims and objectives. Across the world, gas flaring is currently reducing, and many countries are introducing new strategies like emission or anti-flaring policies and taxes to reduce gas wastage and pollution.

Novel/Additive Information
The government, on the other hand, needs to intervene by passing into law appropriate bills and implementing policies formulated in regards to the oil and gas industry. Closely analyzing monetization and Offshore LNG, a new understanding of the neglected issue of Supply Chain Management will be established for economic growth. This paper gives an insight on the FLNG, by looking into FLNG publications and some contributions from several energy studies such as the Institute of Energy Studies and others.
A Calculation Model for the Temperature Field of the Shallow Submarine Strata Considering the Heat of Hydration of Cement Slurry
Authors: Diao Haoyu , Fan Honghai , Leira Bernt Johan , Sangesland Sigbjørn , Ye Yuguang , Liu Yuhan , Zhou Fei , wu Bangchen , Sevillano Lucas Cantinelli , Yao Changqing 
Published: April 2022

Abstract
During offshore oil and gas resource exploration, the large amount of heat generated by cement hydration will cause the hydrates around the wellbore to decompose, leading to cementing operation failure or more serious types of accidents. Therefore, the influence of the heat on temperature of hydrate layer, overlying and underlying strata during the cementing process is studied in this paper. A calculation model for the temperature field of deep-water hydrate layer cementing is established. The model considers the influence of cement slurry hydration heat release, hydrate decomposition, and heat transfer between hydrate layer, overlying and underlying strata on temperature distribution of the hydrate layer, overlying and underlying strata. Using MATLAB language programming, the partial differential equations were solved by the difference method, and numerical simulations were carried out through simulated wells. The temperature distribution of drilling fluid, cement slurry, hydrate layer and strata during the deep-water cementing process is calculated. Through analysis, the following conclusions are obtained: 1. The cement hydration in the cementing process generates a lot of heat, which severely destroys the stable temperature and pressure conditions of the hydrate layer and causes a large amount of decomposition of the hydrate; 2. The decomposition of hydrate is a long-term process comparing with the cement hydration process. Therefore, the decomposition of hydrate during the cementing operation and for a period of time after completion will bring safety threats to the drilling and completion operations; 3. Considering the heat transfer between hydrate layer, overlying and underlying strata is more accurate to reflect the temperature change of the hydrate layer during the cementing process than only considering the heat exchange between the cement column and the hydrate layer; 4. Reducing the volume of the annulus between the conductor casing and the surface casing can effectively reduce the heat of hydration of the cement slurry, which is beneficial in order to reduce the impact of hydrate decomposition, so it is recommended to use a casing combination with a smaller annulus in the cementing through the hydrate layer. The models studied in this paper can more accurately predict the deep-water cementing temperature field of hydrate layers, provide safety guidance for cementing design in deep-water hydrate layer cementing operations, and lay a foundation for deep-water drilling stability studies.
Predict Drilling Equipment Failure Using AI-Based Sound Waive Analysis Methodology
Authors: Alsaif Saif Abdulmohsen , Alothman Tameem Saud 
Published: April 2022

Abstract
Using AI-Based sound wave analysis of drilling equipment to assess its health condition and to predict equipment failure by detecting anomalous sound patterns in both time and frequency domains, and apply predictive maintenance.
Machines can produce noise with frequencies higher than the upper audible limit of human hearing, which is referred to as ultrasound (or ultrasonic sound). Thus, by listening to a wider sound spectrum, a better understanding of equipment state is achieved; and will lead to more accurate failure prediction methods. The process starts by capturing sounds via microphone. Then, Short Time Fourier Transform is used to convert time domain sound wave to its corresponding frequency domain. Both time and frequency domain signals are combined to form a two-dimensional spectrogram. This spectrogram is trained using an AI model to learn the difference between normal and abnormal equipment sounds. After training, the system identifies anomalous sounds the equipment might produce. Hence, generate an alert to the operational team to take actions, preventing equipment failure.
Compared to the human auditory system, the experimental results showed that the proposed method achieved significant improvement in anomalous sounds detection only for machines that can produce noise in the ultrasound region, while other machines achieved worse results compared to the audible sound region.
Evolution in the Development of Pre-Salt Carbonate Drill Bits in the Santos Basin
Authors: Lima Flank Melo de , Passos Adriano Gouveia Lima Gomes dos 
Published: April 2022

Abstract
The pre-salt reserves offshore from Santos basin represent a great opportunity and probably the most important recent oil discovery in Brazil. These carbonate reservoirs are currently drilled with various types of drill bits, and have proven to be a challenging environment. Since their discovery, there has been an incessant search for the development of drill bits that are able to drill these hard and, in some cases, very abrasive formations in a single run and with optimized drilling rates. In this way, the costs for wells construction would be increasingly reduced, which would further increase the attractiveness of the development of these fields in Santos basin. This paper presents the technological evolution employed in drill bits, from the beginning of the exploratory campaign in Santos basin until newer developments, newer PDC bits designs, and geometric cutters currently used in pre-salt carbonate drilling. In addition, the contractual improvements and results are also presented, showing consistent evolution of ROP and perforated extension over the years, with the development and use of new drill bits in Petrobras.
Pile Driving in Heavily Overconsolidated Clays
Authors: Stevens Robert F. , Millan Carlos , Gupta Umesh , Park Gavin 
Published: April 2022

Abstract
Results are presented for the driving of 48-in.-diameter open-ended piles in heavily overconsolidated clay for a fixed offshore platform located about 28 miles off the northeast coast of Trinidad. A comparison of observed and predicted blow counts, measured maximum driving stresses, the energy transmitted to the pile, and the soil resistance to driving for different damping factors are presented. The results of signal matching analyses also are presented.