bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative Hyperbolic Cutting Structure Brings Step Change in Drilling Efficiency Onshore Mexico
Authors: Rosique P. , Anguiano S. , Tocantins J. P. , Ross J. , Luna O. 
Published: June 2023

Abstract
The discovery of field T in Mexico represented the largest such find in a generation. Hence, drilling activity has been focused primarily on economically viable ways to develop these reserves. The reservoir poses several drilling challenges, such as lack of drill bit cutting structure, durability, and aggressiveness leading to unwanted bottomhole assembly trips. These challenges lead to increased well construction costs. Accordingly, an application-specific bit design needed to be developed to optimize drilling efficiency in this section. This complex drilling scenario demanded a comprehensive rock characterization study to accurately diagnose the root causes for the low drilling efficiency. To determine the environmental factors that influence bit performance, a detailed formation mapping analysis was conducted using an engineering program for rock strength identification from offset wells. This information was then used to calibrate the digital formation file inside the integrated dynamic design and analysis software, capable of reproducing actual drilling conditions. The virtual model was used to develop a specific drill bit design equipped with cutting edge 3D-cutter, optimizing performance well beyond conventional fixed and flat cutters.Results from the well D2 indicate that this innovative technology yielded superior overall drilling performance compared to best offsets and has become the new benchmark for this application in Mexico. The comprehensive planning and detailed engineering analysis led to outstanding operational execution, setting new standards for drilling performance, reducing nonproductive time drastically and therefore minimizing CO2 emissions. The customized bit design drilled the longest 10 ⅝-in run in the field. This unprecedent performance led to 29% improvement in rate of penetration when compared to conventional Polycrystalline Diamond Compact (PDC) drill bit models, reducing rig time by 5.7 days exceeding customer expectations. The learning framework was applied using post-well analysis to compare model predictions with drilling data to further refine the model and close the loop on the original calibration, paving the way for further evolution of the bit design.A successful methodology for drill bit development aimed at drilling efficiency improvement was applied using a new cutting element (hyperbolic diamond element) and novel design concepts that replaced the traditional trial-and-error methods. Testing each new design feature virtually and running parameter sensitivity analyses to ensure a wide margin of applicability, the task was made much easier by the development of a calibrated virtual formation model in a fully traceable and replicable process.
A Game-Changing Strategy to Increase the Production Tubing Run Life in a Highly Carbon-Dioxide Corrosive Environment: Shushufindi-Aguarico Fields Case Study
Authors: Romero C. , Estevez D. , Espinosa C. , Freire C. , Sierra M. C. , Aguilar L. , Rodriguez R. , Sepulveda W. , Somale J. 
Published: June 2023

Abstract
Since the beginning of production in Shushufindi Field, Ecuador, one of the main reasons for well intervention has been issues with the production tubing integrity. More than 30% of production tubing failures were related to corrosion in the tubing, generating additional operational expenditures and production losses. Our strategy to increase the production tubing run life in the field is presented.
In 2020, an incremental increase in field production was also accompanied by an increase in production tubing failures. Based on failure analysis that included laboratory tests, information analysis, run-life history, and simulations to predict the corrosion velocity, it was possible to identify the critical wells and to migrate the tubing grade from a L80Cr1 to a grade with 3% chromium (Cr) and maintain the use of an internal flush connection.
Before 2018, the common material used for the tubing in Shushufindi was carbon steel API N80.Q and the connection was API EU. Since November 2017 the failure index started to increase, leading to the massification of the grade L80 with 1% Cr content and an internal flush premium connection.
In 2020, the total production volume losses attributable to production tubing problems were 8%, and the average run life of wells that failed because of production tubing integrity was less than 400 days, compared to electric submersible pump (ESP) failures.
With the massive implementation of 1% Cr steel grade in 2018 and an internal flush premium connection in the tubing, the failure index was reduced from 0.33 in July 2019 to 0.14 in January 2021. However, the use of reused pipe and the strategy to increase production in the field by commingling formations and upsizing the pumps, created a more demanding condition, and induced new tubing failures.
With these new operating conditions, a strategy to mitigate early failures was to install tubing with 3% Cr content in seven critical wells. By now the tubing run life had been doubled in two wells and overlapped the previous run life in four wells.
Using a 3% Cr-grade tubing has helped to reduce the interventions by three times, and production losses have been reduced by 72,000 bbl. An opportunity to reuse pipe was identified when the tubing was recovered in perfect condition in a pullout caused by an ESP failure after 200 days. Currently (February 2023) the failure index due to communication tubing casing is 0.06.
Attributing practice variation by its sources: the case of varicose veins treatments in the Netherlands
Authors: Schippa Luca , Gaspar Katalin , Hijden Eric , Koolman Xander 
Published: June 2023

Abstract
Background
Unwarranted practice variation refers to regional differences in treatments that are not driven by patients’ medical needs or preferences. Although it is the subject of numerous studies, most research focuses on variation at the end stage of treatment, i.e. the stage of the treating specialist, disregarding variation stemming from other sources (e.g. patient preferences, general practitioner referral patterns). In the present paper, we introduce a method that allows us to measure regional treatment variation with that at different stages of the patient journey leading up to treatment.
Methods
A series of logit regressions estimating the probability of (1) initial visit with the physician and (2) treatment correcting for patient needs and patient preferences. Calculating the coefficient of variation (CVU) at each stage of the patient journey.
Results
Our findings show large regional variations in the probability of receiving an initial visit, The CVU, or the measure of dispersion, in the regional probability of an initial visit with a specialist was significantly larger (0.87–0.96) than at the point of treatment both conditional (0.14–0.25) and unconditional on an initial visit (0.65–0.74), suggesting that practice variation was present before the patient reached the specialist.
Conclusions
Our finding demonstrate that specialists’ decisions meaningfully diminish the amount of regional variation, but the variation does not entirely disappear at any stage, even after controlling for patient needs and patient preferences. Hence, a significant share of the treatment variation remains ‘unexplained’. Our findings also suggest that at least of the variation stems from the regional variation in providing referrals in Dutch primary care.
JEL classification
I11; I13; I18
The Labrador Sea sets a new reference point in the subpolar North Atlantic climate record
Authors: Yashayaev Igor 
Published: June 2023

Abstract
The Labrador Sea is the deepest, coldest and freshest subpolar North Atlantic basin. Here, open-ocean convection, driven by surface winter cooling, produces Labrador Sea Water (LSW), a dense voluminous water mass spreading across the ocean, filling and ventilating its intermediate-depth reservoir, and contributing to the Atlantic Meridional Overturning Circulation. The recent multiyear development of recurrently-deepening convection was initiated by increased winter cooling in 2012, continued past 2015, having 1994-2023-high surface cooling, and reached 2000 m, 1996–2023 record deep, in 2018. The convective deepening during 2016–2018 owes to water-column preconditioning by previous winter convections. Convection shallowed in the following winters completing the formation of the densest and largest LSW class since the mid-1990s. The most abrupt shifts in the Labrador Sea convection intensities and depths since the mid-1990s occurred in 2021 and 2023, when winter mixing could only reach 800 m and 700 m, respectfully, shallowing by more than 800 m from 2020 and 2022, and becoming the shallowest since 2011. Consequently, the entire intermediate layer has recently warmed and become less dense. The mentioned cases of abruptly shallowed convection and rapidly warmed ocean can be attributed to the 2021 and 2023 winter collapses of the Polar Vortex, which weakened and reversed the westerly winds, bringing anomalously warm air to the Labrador Sea, reducing the surface cooling to the lowest since 2010, and consequently inhibiting convection.
Simulation-guided Development of an Optical Calorimeter for High Dose Rate Dosimetry
Authors: Roberts Jackson , Moggre Alicia , Meyer Juergen , Marsh Steven 
Published: June 2023

Abstract
PURPOSE
Optical Calorimetry (OC) is based on interferometry and provides a direct measurement of spatially resolved absorbed dose to water by measuring refractive index changes induced by radiation. The purpose of this work was to optimize and characterize in software an OC system tailored for ultra-high dose rate applications and to build and test a prototype in a clinical environment.
METHODS
A radiation dosimeter using the principles of OC was designed in optical modelling software. Traditional image quality instruments, fencepost and contrast phantoms, were utilized in both software and experimentally in a lab environment to investigate noise reduction techniques and to test the spatial and dose resolution of the system. Absolute dose uncertainty was assessed by measurements in a clinical 6 MV flattening filter free (FFF) photon beam with dose rates in the range 0.2–6 Gy/s achieved via changing the distance from the source.
RESULTS
Design improvements included: equalizing the pathlengths of the interferometer, isolating the system from external vibrations and controlling the system’s internal temperature as well as application of mathematical noise reduction techniques. Simulations showed that these improvements should increase the spatial resolution from 22 to 35 lp/mm and achieve a minimum detectable dose of 0.2 Gy, which was confirmed experimentally. In the FFF beam, the absolute dose uncertainty was dose rate dependent and decreased from 2.5 ± 0.8 Gy to 2.5 ± 0.2 Gy for dose rates of 0.2 and 6 Gy/s, respectively.
CONCLUSIONS
A radiation dosimeter utilizing the principles of OC was developed and constructed. Optical modelling software and image quality phantoms allowed for iterative testing and refinement. The refined OC system proved capable of measuring absorbed dose to water in a linac generated photon beam. Reduced uncertainty at higher dose rates indicates the potential for OC as a dosimetry system for high dose rate techniques such as microbeam and ultra-high dose-rate radiotherapy.
Determining structures of individual RNA conformers using atomic force microscopy images and deep neural networks
Authors: Wang Yun-Xing , Degenhardt Maximilia , Degenhardt Hermann , Bhandari Yuba , Lee Yun-Tzai , Ding Jienyu , Heinz William , Stagno Jason , Schwieters Charles , Zhang Jinwei 
Published: June 2023

Abstract

The vast percentage of the human genome is transcribed into RNA, many of which contain various structural elements and are important for functions. RNA molecules are conformationally heterogeneous and functionally dyanmics1, even when they are structured and well-folded2, which limit the applicability of methods such as NMR, crystallography, or cryo-EM. Moreover, because of the lack of a large structure RNA database, and no clear correlation between sequence and structure, approaches like AlphaFold3 for protein structure prediction, do not apply to RNA. Therefore determining the structures of heterogeneous RNA is an unmet challenge. Here we report a novel method of determining RNA three-dimensional topological structures using deep neural networks and atomic force microscopy (AFM) images of individual RNA molecules in solution. Owing to the high signal-to-noise ratio of AFM, our method is ideal for capturing structures of individual conformationally heterogeneous RNA. We show that our method can determine 3D topological structures of any large folded RNA conformers, from ~200 to ~420 residues, the size range that most functional RNA structures or structural elements fall into. Thus our method addresses one of the major challenges in frontier RNA structural biology and may impact our fundamental understanding of RNA structure.
Modeling and optimization of triclosan biodegradation by the newly isolated Bacillus sp. DL4: Kinetics and metagenomics analysis
Authors: Li Xuejie , Hu Xiao-Min , Zhao Xin , Wang Fan , Zhao Yan 
Published: June 2023

Abstract

Overusing triclosan (TCS) endangered ecological safety and human health, and the pandemic of COVID-19 aggravates the accumulation of TCS in the aquatic environment. Therefore, reducing residual TCS concentrations in the environment is an urgent issue. An aerobic bacterium, Bacillus sp. DL4 was isolated with the capability of TCS biodegradation. Response surface methodology (RSM) and artificial neural network (ANN) were carried out to optimize and verify the different condition variables. All the variables were linear and the interaction of the three factors significantly affected TCS removal at the quadratic level (p < 0.001). Under the optimal conditions (35℃, initial pH 7.31, and 5% strain DL4), the TCS removal rate of 95.89 ± 0.68% was observed and found to be consistent with the predicted values from RSM and ANN models. In addition, statistical comparisons between the models indicated that the ANN model had a stronger predictive capability than the RSM model. Kinetic studies showed that TCS degradation was consistent with a pseudo-first-order kinetic model. Whole genome sequencing indicated that many functional genes were involved in and facilitated TCS degradation. Main metabolite products were detected and identified during the biodegradation process by LC-MS, and a possible degradation pathway was tentatively hypothesized. Overall, this study provides a theoretical foundation for the characterization and mechanism of TCS biodegradation in the environment by Bacillus sp. DL4.
A systematic review and meta-analysis of clinical efficacy of early and late rehabilitation interventions for ischemic stroke
Authors: Wei Xufang , Sun Shengtong , Zhang Manyu , Zhao Zhenqiang 
Published: June 2023

Abstract
Introduction: At present, stroke has become the first cause of death and disability among Chinese adults. With the coming of the aging population in China, the disease burden brought by stroke will be increasingly aggravated. And stroke is a leading cause of disability. There is a golden plastic period after stroke, during which timely and safe intervention and rehabilitation therapy can effectively improve the disability status. However, there is still controversy about the duration of interventional rehabilitation after stroke. This study conducted a meta-analysis on the influence of intervention in early and late ischemic stroke rehabilitation.
Method: Chinese language databases such as CNKI, Wanfang, and VIP, and English language databases such as PubMed, Web of Science, and The Cochrane Library were searched, and RCT related to early and late rehabilitation of ischemic stroke from the establishment of the database to May 2022 was collected. Review Manager 5.4.1 was used for relevant analysis.
Results: A total of 1635 patients were included in 14 studies. The results showed that, compared with late rehabilitation, early rehabilitation improved clinical efficacy. Barthel Index or Modified Barthel Index score was [MD=8.82, 95%CI(8.21,9.43), p < 0.001]; the score of Fugl-Meyer Assessment Scale was [MD=8.75, 95%Cl (7.0,10.47), P< 0.001]; the score of NIHSS was [MD=-1.42, 95% CI(-1.93,-0.91), P<0.001]; the result of China Stroke Scale score was [MD=-3.68, 95%CI(-5.43,-1.92), P<0.001].
Conclusion: In comparison with late rehabilitation, early rehabilitation can significantly improve self-care abilities, daily activities, and neurological functions of ischemic stroke patients.
Registration: This meta-analysis has been registered with Prospero, and the registration number is CRD42022309911. The registration period is March 22, 2022.
Network of Drones for Early Warning of Forest Fire and Dynamic Fire Quenching Plan Generation
Authors: S Manoj , Valliyammai C. 
Published: June 2023

Abstract
Wildfires, one of the most frequent natural disasters, significantly harm society, the economy, and the environment. Transfer learning algorithm and modern machine learning tools can help in early forest fire prediction, detection, and dynamic fire quenching. Also, a dynamic fire quenching plan is prescribed which takes into account the live status of forest fire. A network of drones which has high definition image processing and decision making capabilities are used for detection of forest fire in the very early stage there by preventing the forest fire. In case fire breaks out, the proposed system generates a fire quenching plan and alerts the fire and rescue departments so that they do plan early and stop the forest fire as soon as possible. ResNet, VGGNet, Mobile Net, Alexi Net, GoogLeNet models enhanced with transfer learning are used to predict the forest fire events in India. It is found that the proposed technique GoogLeNet-TL, which uses transfer learning with GoogLeNet has resulted in 96% accuracy and 97.56% F1 score than other models considered for forest fire prediction in Indian subcontinent.
Using stable isotopes and gut contents to investigate the foraging ecology of green turtles (Chelonia mydas) in New Caledonia
Authors: Read Tyffen C. , Wantiez Laurent , Keller Florent , Werry Jonathan M , de Merwe Jason P. van , Chateau Olivier , Farman Richard , Limpus Colin J. 
Published: June 2023

Abstract
Green sea turtles (Chelonia mydas) face many threats from anthropogenic activity, and are listed as Endangered on the International Union for the Conservation of Nature (IUCN) Red List of Threatened Species. They spend the majority of their lives in coastal foraging areas, and show strong fidelity to narrow foraging ranges. Understanding the foraging ecology of green turtles is therefore important for their management and conservation. Using stable isotopes analysis (n = 179) and identification of stomach contents (n = 21), this study investigated the foraging ecology of four distinct green turtle foraging populations (Goro, Isle of Pines, Ouen Island and Uo/Mato Islands) within the Grand Lagon Sud. This World Heritage Area located in New Caledonia supports regionally important nesting and foraging green turtle populations. The δ13C and δ15N values of skin samples ranged from − 19.3‰ to -7.3‰ and 2.8‰ to 15.9‰, respectively. Bayesian mixing model indicated mixed diets that were significantly different between locations, indicating the need for customised management strategies for green turtles in this area. There was generally a preference for an algal diet, and significant consumption of animal matter at all locations. This was generally supported by the stomach contents analyses, although not always, illustrating the importance of investigating SIA and stomach contents. This study provides important information on the foraging ecology of green turtles in New Caledonia, supporting management outcomes in this region. This collaboration with the tribes of the Grand Lagon Sud is also the first step towards the integrated management of the resource.
Restricting datasets to classifiable samples augments
discovery of immune disease markers
Authors: Glehr Gunther , Riquelme Paloma , Kronenberg Katharina , Lohmayer Robert , Lopez-Madrona Victor , Kapinsky Michael , Schlitt Hans , Geissler Edward , Spang Rainer , Haferkamp Sebastian , Hutchinson James 
Published: June 2023

Abstract

Immunological diseases are typically heterogeneous in clinical presentation, severity and response to therapy. Markers of immune diseases often reflect this variability, especially compared to their regulated behavior in health. This leads to a common, unarticulated problem that frustrates marker discovery and interpretation: Unequal variance of immune disease marker expression between patient classes necessarily limits a marker’s informative range. To solve this problem, we introduce dataset restriction, a procedure that splits datasets into classifiable and unclassifiable samples. Applied to synthetic flow cytometry data, restriction identified markers that were otherwise disregarded. In advanced melanoma, restriction found new markers of immune-related adverse event risk after immunotherapy and enabled multivariate models that accurately predicted immunotherapy-related hepatitis. Hence, dataset restriction augments discovery of immune disease markers, increases predictive certainty for classifiable samples and improves multivariate models incorporating markers with a limited informative range. This principle can be directly extended to any classification task.
Study of potential anti-bronchial asthma substances in Huagai San based on in vitro and in vivo substance analysis and network pharmacology
Authors: Zhou Nan , Wang Ran , Liu Linfeng , Liu Wei , Luo Xiaojian , rao xiaoyong , He Mingzhen 
Published: June 2023

Abstract
Huagai San(HGS) is an herbal compound commonly used in the treatment of bronchial asthma. Although its effectiveness has been demonstrated in clinical applications, current research on HGS has focused on its clinical efficacy, with a lack of systematic material basis studies of the components. The mechanism of action and bioactive components of HGS are still unknown. In this study, we propose an integrated strategy based on in vivo and in vitro substance analysis and network pharmacology. The aim of this study is to elucidate the chemical composition, clarify the constituents absorbed in the blood, predict the main bioactive components, discovery of potential therapeutic targets, and use it in the study of potential anti-bronchial asthma substances for HGS. A four-step filtering strategy was established by using UHPLC-Q-TOF-MS/MS and applied to the identification of the chemical composition of HGS. 185 compounds were analyzed in the herbal components, and 65 compounds including 40 prototypes and 25 metabolic products were identified in rats. Based on the in vivo composition analysis of HGS, the bioactive components and potential therapeutic targets in the treatment of bronchial asthma were investigated by network pharmacological analysis. The results provide a scientific basis for understanding the bioactive components of HGS and their pharmacological mechanisms.