bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolutionary game equilibrium in the downstream carbon market: Evidence from the household size in China
Authors: Qi Xiaoyuan , Han Ying , Jin Baoling 
Published: February 2023

AbstractCarbon trading downstream, as a key strategy for decreasing carbon emissions, has the potential to hasten the entire society's decarbonization. Taking the government, household, and carbon trading management center as stakeholders, this paper constructs a tripartite evolutionary game model, examines and stimulates evolutionary stability strategies, and then proposes some policy implications. Findings show that the downstream carbon market faces a complex evolutionary process. The promotion of the policy can be split into two periods: policy promotion and policy stability implementation. And proper household size management is a crucial and effective strategy to encourage downstream carbon trading programs and emission reduction.
Health‐related experiences of adults with chronic cough: Empirical research mixed methods
Authors: Weiner Michael , Weaver Jessica , Gowan Tayler , Baird Sean A. , Huffman Monica , Dexter Paul , Bali Vishal , Schelfhout Jonathan , Griffith Ashley , Pell Jacob , Doshi Ishita , Talib Tasneem 
Published: February 2023

AbstractAimTo describe adults' health‐related experiences with chronic cough.DesignSurvey and interviews.MethodsParticipants completed questionnaires and interviews, to explore chronic cough's impact and management.Data SourcesPatients aged 18–85 years with at least three cough‐related encounters within 56–120 days.ResultsForty‐one patients were surveyed. Mean cough severity was 4.5 (scale 0–9). Chronic cough‐related problems included embarrassment (66%), fatigue (56%), and anxiety or depression (49%). Testing was judged insufficient by 44%. Only 28% were satisfied with treatment; 20% reported abandoning treatment due to ineffectiveness. Interview themes (N = 30) included frustration with diagnostic uncertainty, and feelings of therapeutic futility. Some reported psychological distress. Work and socializing were commonly disrupted.ConclusionDiagnostic uncertainty, perceived limitations of testing, and treatment failures suggest needs for better approaches to evaluating and treating chronic cough. Special attention to identifying and addressing mental health issues appears warranted.
Establishing the Ideal Conditions to Create an Airway Fire Using a Porcine Airway Model
Authors: Bysice Andrew M. , Oswald Tyler , Vasquez Luis E. Mendoza , Laxague Francisco , Elise Graham M. , Noppens Ruediger , Fung Kevin 
Published: February 2023

AbstractObjectiveAirway fires are a rare but devastating complication of airway surgery. Although protocols for managing airway fires have been discussed, the ideal conditions for igniting airway fires remain unclear. This study examined the oxygen level required to ignite a fire during a tracheostomy.Study DesignPorcine Model.SettingLaboratory.MethodsPorcine tracheas were intubated with a 7.5 air‐filled polyvinyl endotracheal tube. A tracheostomy was performed. Monopolar and bipolar cautery were used in independent experiments to assess the ignition capacity. Seven trials were performed for each fraction of inspired oxygen (FiO2): 1.0, 0.9, 0.7, 0.6, 0.5, 0.4, and 0.3. The primary outcome was ignition of a fire. The time was started once the cautery function was turned on. The time was stopped when a flame was produced. Thirty seconds was used as the cut‐off for “no fire.”ResultsThe average time to ignition for monopolar cautery at FiO2 of 1.0, 0.9, 0.8, 0.7, and 0.6 was found to be 9.9, 6.6, 6.9, 9.6, and 8.4 s, respectively. FiO2 ≤ 0.5 did not produce a flame. No flame was created using the bipolar device. Dry tissue eschar shortened the time to ignition, whereas moisture in the tissue prolonged the time to ignition. However, these differences were not quantified.ConclusionDry tissue eschar, monopolar cautery, and FiO2 ≥ 0.6 are more likely to result in airway fires.
Disconnection from nature: Expanding our understanding of human–nature relations
Authors: Beery Thomas , Stahl Olafsson Anton , Gentin Sandra , Maurer Megan , Stålhammar Sanna , Albert Christian , Bieling Claudia , Buijs Arjen , Fagerholm Nora , Garcia‐Martin Maria , Plieninger Tobias , M. Raymond Christopher 
Published: February 2023

AbstractThe human relationship with nature is a topic that has been explored throughout human history. More recently, the idea of connection to nature has merged as an important transdisciplinary field of study. Despite increased scholarly attention to connection to nature, the notion of disconnection from nature remains undertheorized and understudied.In this perspective article, we argue for a more comprehensive understanding of disconnection from nature to strengthen theories of human‐nature relationships that goes beyond individual relationships and considers social and collective factors of disconnection, including institutional, socio‐cultural and power dimensions.Drawing on case insights, we present the ‘wheel of disconnection’ to illustrate how disconnections from nature manifest across individual or societal meaning‐making processes, thereby problematizing existing research that seeks to create dualisms between human positive and negative impacts on the environment in isolation from cultural or political contexts.We do not seek to discount research or important practical efforts to foster an individual's connection to nature by elevating disconnection. Instead, we hope that creating greater awareness and understanding of disconnection will be able to guide opportunities going forward for strengthening a connection to nature along a continuum from the individual to the social.Read the freePlain Language Summaryfor this article on the Journal blog.
Thermochromic and temperature regulation properties of phase change materials derived from polymer composites loaded with VO2 particles
Authors: Srirodpai Onruthai , Wootthikanokkhan Jatuphorn , Nawalertpanya Saiwan 
Published: February 2023

AbstractThis research work concerns the development of phase change materials based on poly(ethylene terephthalate) (PET) mixed with vanadium dioxide particles (VO2). Monoclinic VO2 particles were synthesized via a hydrothermal process followed by modification of the particle surface with a silane coupling agent, namely 3‐(aminopropyl) triethoxysilane (APTES). After that, the metal oxide particles were mixed with PET flakes, derived from used PET bottles, in an internal mixer. In this study, the effects of surface modification and concentrations of VO2 particles on thermomechanical and optical properties of the composites were investigated. From the DSC results, it was found that the percentage crystallinity of PET increased after loading with VO2. This indicates that VO2 can act as a nucleating agent inducing the crystallization of the PET chains. From the scanning electron microscopy with energy dispersive X‐ray spectroscopy (SEM–EDX) images, better dispersion of VO2 particles in the PET matrix was noticed when the surface‐modified VO2 particles were used as a replacement for the normal VO2 particles. This contributed to the greater percentage of visible light transmittance through the composite sheets. Thermogravimetric analysis (TGA) profiles of both PET and PET/VO2 specimens are similar, indicating that the VO2 did not accelerate the thermal decomposition of the PET. When the specimens were exposed to an IR lamp, it was found that the temperature behind the PET/VO2 sheets dropped when compared to that of the neat PET sheets. Some shrinkage and deformation of the PET/VO2 specimens were also noticed. The higher the VO2 loading, the greater the deformation. The effect was ascribed to the fact that the actual temperature was above the critical transition temperature of VO2. Consequently, the NIR transmittance was suppressed at the expense of the greater NIR absorbance by the VO2 phase in the composites. Finally, when the specimens were exposed to solar irradiation at ambient temperature, the temperature underneath the PET/VO2 specimens became greater than that of the control specimen (the neat PET). The result was discussed in the light of the emissivity of VO2 at ambient temperature, which is considerably low. Overall, this study demonstrates that PET/VO2 can exhibit both cooling and warming effects, depending on the ambient temperature in relation to the critical transition temperature (Tc) of VO2.
Cepacia syndrome in cystic fibrosis: A systematic review of the literature and possible new perspectives in treatment
Authors: Daccò Valeria , Alicandro Gianfranco , Consales Alessandra , Rosazza Chiara , Sciarrabba Calogero S. , Cariani Lisa , Colombo Carla 
Published: February 2023

AbstractBackgroundCepacia syndrome (CS) is an acute, necrotizing pneumonia with a high mortality rate, occurring in patients with cystic fibrosis (CF) infected with Burkholderia cepacia complex (BCC). Due to its low incidence, data on this condition are limited.MethodsWe conducted a systematic review of the reported cases of CS by searching MEDLINE, Embase and the Cochrane Library to improve knowledge of this rare but potentially lethal condition.ResultsWe included 15 eligible articles, describing 18 cases (9 females) of CS. Median age at onset was 22 years (range: 10–60 years); median time to CS after first infection by BCC was 5 years (range: 1–26 years). Burkholderia cenocepacia was the most frequently reported causative agent. All patients received intravenous antibiotic treatment (most frequently including cotrimoxazole), while inhaled antibiotics were used in five patients (27.8%). Immunosuppressant agents were the most commonly prescribed supportive treatment (n = 7, 38.9%). Half of the patients died (9/18, 50%).ConclusionsThis study describes epidemiological, clinical characteristics, and prognosis of CS cases reported over the last 24 years. CS is a rare yet severe complication of BCC infection in patients with CF, which occurs several years after BCC colonization and has a negative outcome in 50% of the patients. Data are too scanty to identify the most effective therapeutic approach.
A cumulative exposure model for remaining useful life prediction of pitot tube based on dynamic operating data
Authors: Wang Bowen , Sun Jianzhong , Chen Dan , Ning Shungang 
Published: February 2023

AbstractThe data measured by the pitot tube (PT) is related to airspeed indication and flight safety. However, there are few methods to solve the problem of failure prediction and predictive maintenance of PT. This study proposes a method for predicting the remaining useful life (RUL) of the PT based on dynamic operating data. First, an exposure index (EI) characterizing the severity level of operating conditions is proposed based on multiple dynamic operating and environmental parameters, then a cumulative exposure model (CEM) is developed to calculate the cumulative exposure. Dynamic covariate information is incorporated into the time‐to‐failure distribution of PT through the CEM, the RUL distribution of the individual PT is then obtained by Monte Carlo simulation. A case study is carried out based on actual data of a commercial aircraft fleet and shows that the proposed CEM can effectively use historical aircraft environmental information and truncated failure data of the components. The relative error of the remaining life prediction is substantially improved compared to the traditional reliability analysis methods, which means that the proposed model can provide more reliable RUL results based on historical operating conditions, providing better support for PT risk assessment and condition‐based maintenance decisions.
Subcutaneous and muscle layer seroma complicated with thoracentesis
Authors: Sekimoto Yasuhito , Kohmaru Makiko , Okuma Tomoko , Tajima Manabu , Sekiya Mitsuaki 
Published: February 2023

Key messageDiagnostic thoracentesis is a basic and relatively safe diagnostic method for patients with pleural effusion. However, complications of thoracentesis are rare and not well known because of the low incidence. Herein, we report a case of subcutaneous and muscle layer seroma following thoracentesis.
Optogenetics and Light-Sheet Microscopy
Authors: Maddalena Laura , Pozzi Paolo , Ceffa Nicolò G. , Hoeven Bas van der , Carroll Elizabeth C. 
Published: February 2023

AbstractLight-sheet microscopy is a powerful method for imaging small translucent samples in vivo, owing to its unique combination of fast imaging speeds, large field of view, and low phototoxicity. This chapter briefly reviews state-of-the-art technology for variations of light-sheet microscopy. We review recent examples of optogenetics in combination with light-sheet microscopy and discuss some current bottlenecks and horizons of light sheet in all-optical physiology. We describe how 3-dimensional optogenetics can be added to an home-built light-sheet microscope, including technical notes about choices in microscope configuration to consider depending on the time and length scales of interest.
Widefield Multiphoton Imaging at Depth with Temporal Focusing
Authors: Wijesinghe Philip , Dholakia Kishan 
Published: February 2023

AbstractOptical imaging has the potential to reveal high-resolution information with minimal photodamage. The recent renaissance of super-resolution, widefield, ultrafast, and computational imaging methods has broadened its horizons even further. However, a remaining grand challenge is imaging at depth over a widefield and with a high spatiotemporal resolution. This achievement would enable the observation of fast collective biological processes, particularly those underpinning neuroscience and developmental biology. Multiphoton imaging at depth, combining temporal focusing and single-pixel detection, is an emerging avenue to address this challenge. The novel physics and computational methods driving this approach offer great potential for future advances. This chapter articulates the theories of temporal focusing and single-pixel detection and details the specific approach of TempoRAl Focusing microscopy with single-pIXel detection (TRAFIX), with a particular focus on its current practical implementation and future prospects.
The Suitability of Different Training Images for Producing Low Connectivity, High Net:Gross Pixel-Based MPS Models
Authors: Walsh Deirdre A. , López-Cabrera Javier , Manzocchi Tom 
Published: February 2023

AbstractPixel-based multiple-point statistical (MPS) modelling is an appealing geostatistical modelling technique as it easily honours well data and allows use of geologically-derived training images to reproduce the desired heterogeneity. A variety of different training image types are often proposed for use in MPS modelling, including object-based, surface-based and process-based models. The purpose of the training image is to provide a description of the geological heterogeneities including sand geometries, stacking patterns, facies distributions, depositional architecture and connectivity. It is, however, well known that pixel-based MPS modelling has difficulty reproducing facies connectivity, and this study investigates the performance of a widely-available industrial SNESIM algorithm at reproducing the connectivity in a geometrically-representative, idealized deep-water reservoir sequence, using different gridding strategies and training images. The findings indicate that irrespective of the sand connectivity represented in the training image, the MPS models have a percolation threshold that is the same as the well-established 27% percolation threshold of random object-based models. A more successful approach for generating poorly connected pixel-based MPS models at high net:gross ratios has been identified. In this workflow, a geometrical transformation is applied to the training image prior to modelling, and the inverse transformation is applied to the resultant MPS model. The transformation is controlled by a compression factor which defines how non-random the geological system is, in terms of its connectivity.
Artifacts in Localised Multivariate Uniform Conditioning: A Case Study
Authors: Rondon Oscar , Talebi Hassan 
Published: February 2023

AbstractLocalised Multivariate Uniform Conditioning (LMUC) is a technique designed for spatially locating Selective Mining Unit (SMU) grades derived using Multivariate Uniform Conditioning (MUC) for the assessment of recoverable resources. LMUC has the advantage of producing SMU estimates conforming to the MUC panel-specific grade-tonnage curves while preserving the spatial grade distribution at the selective mining level. However, LMUC results have two severe artifacts. This paper documents both artifacts using four grades from a large nickel–cobalt laterite deposit in Western Australia.
Applying Clustering Techniques and Geostatistics to the Definition of Domains for Modelling
Authors: de Castro Moreira Gabriel , Costa João Felipe Coimbra Leite , Marques Diego Machado 
Published: February 2023

AbstractMachine learning is a broad field of study that can be applied in many areas of science. In mining, it has already been used in many cases, for example, in the mineral sorting process, in resource modeling, and for the prediction of metallurgical variables. In this paper, we use for defining estimation domains, which is one of the first and most important steps to be taken in the entire modeling process. In unsupervised learning, cluster analysis can provide some interesting solutions for dealing with the stationarity in defining domains. However, choosing the most appropriate technique and validating the results can be challenging when performing cluster analysis because there are no predefined labels for reference. Several methods must be used simultaneously to make the conclusions more reliable. When applying cluster analysis to the modeling of mineral resources, geological information is crucial and must also be used to validate the results. Mining is a dynamic activity, and new information is constantly added to the database. Repeating the whole clustering process each time new samples are collected would be impractical, so we propose using supervised learning algorithms for the automatic classification of new samples. As an illustration, a dataset from a phosphate and titanium deposit is used to demonstrate the proposed workflow. Automating methods and procedures can significantly increase the reproducibility of the modeling process, an essential condition in evaluating mineral resources, especially for auditing purposes. However, although very effective in the decision-making process, the methods herein presented are not yet fully automated, requiring prior knowledge and good judgment.
Addressing Application Challenges with Large-Scale Geological Boundary Modelling
Authors: Ball Adrian , Zigman John , Melkumyan Arman , Chlingaryan Anna , Silversides Katherine , Leung Raymond 
Published: February 2023

AbstractFor banded iron formation-hosted deposits accurate boundary modelling is critical to ore-grade estimation. Key to estimation fidelity is the accurate separation of the different domains within the ore body, requiring modelling of the boundaries between domains. This yields both theoretical and application challenges. We present a series of solutions for application challenges that arise when modelling large-scale boundaries employing a composition of Gaussian Process models on exploration and production hole data. We demonstrate these in the banded iron formation-hosted iron ore deposits in the Hamersley Province of Western Australia. We present solutions to several challenges: the inclusion of information derived from a geologist-defined boundary estimate to incorporate domain knowledge in data sparse regions, the incorporation of unassayed production holes that are implicitly defined as waste to augment production hole assay data, and a more holistic method of defining regional bounds and spatial rotations for Gaussian Process modelling of local spaces. Solution are evaluated against a range of metrics to show performance improvements over the manually performed estimation by an expert geologist of the boundaries delineating the ore body domains. Reconcilliation scores are used for evaluating the quality of predicted domain boundaries against measured production data. The predicted and in situ surfaces are also qualitatively evaluated against production data to ensure that the models were evaluated to be geologically sound by an expert in the field. In particular, better fidelity is shown when separating mineralised and non-mineralised ore, consequently improving the estimation of the ore-grades present in the mine site.
Simulation of Stationary Gaussian Random Fields with a Gneiting Spatio-Temporal Covariance
Authors: Allard Denis , Emery Xavier , Lacaux Céline , Lantuéjoul Christian 
Published: February 2023

AbstractThe nonseparable Gneiting covariance has become a standard to model spatio-temporal random fields. Its definition relies on a completely monotone function associated with the spatial structure and a conditionally negative semidefinite function associated with the temporal structure. This work addresses the problem of simulating stationary Gaussian random fields with a Gneiting-type covariance. Two algorithms, in which the simulated field is obtained through a combination of cosine waves are presented and illustrated with synthetic examples. In the first algorithm, the temporal frequency is defined on the basis of a temporal random field with stationary Gaussian increments, whereas in the second algorithm the temporal frequency is drawn from the spectral measure of the covariance conditioned to the spatial frequency. Both algorithms perfectly reproduce the correlation structure with minimal computational cost and memory footprint.
Geometric and Geostatistical Modeling of Point Bars
Authors: Dawuda Ismael , Srinivasan Sanjay 
Published: February 2023

AbstractPoint bar reservoir geology is frequently encountered in oil and gas developments worldwide. Furthermore, point bar geology is encountered in many sites being considered for large scale CO2 injection for sequestration. A comprehensive modeling method that adequately preserves point bar internal architecture and its associated heterogeneities is still not available. Traditional geostatistical methods cannot adequately capture the curvilinear architecture of point bars. Even geostatistical simulation techniques that can be constrained to multiple point statistics cannot capture the architecture of the point bars because they use regular grids to represent the heterogeneity. If heterogeneities like the thinly distributed shale drapes within the point bar are represented using an extremely fine mesh, the computational cost for performing flow modeling escalates steeply. This paper proposes a modeling method that preserves the point bar internal architecture and heterogeneities, without these limitations. The modeling method incorporates a gridding scheme that adequately captures the point bar architecture and heterogeneities, without huge computational costs.