bluuebunny/crossref_metadata_2025_split huggingface dataset:
Economic losses from hurricanes cannot be nationally offset under unabated warming
Authors: Middelanis Robin , Willner Sven N , Otto Christian , Levermann Anders 
Published: October 2022

Abstract
Tropical cyclones range among the costliest of all meteorological events worldwide and planetary scale warming provides more energy and moisture to these storms. Modelling the national and global economic repercussions of 2017’s Hurricane Harvey, we find a qualitative change in the global economic response in an increasingly warmer world. While the United States were able to balance regional production failures by the original 2017 hurricane, this option becomes less viable under future warming. In our simulations of over 7000 regional economic sectors with more than 1.8 million supply chain connections, the US are not able to offset the losses by use of national efforts with intensifying hurricanes under unabated warming. At a certain warming level other countries have to step in to supply the necessary goods for production, which gives US economic sectors a competitive disadvantage. In the highly localized mining and quarrying sector—which here also comprises the oil and gas production industry—this disadvantage emerges already with the original Hurricane Harvey and intensifies under warming. Eventually, also other regions reach their limit of what they can offset. While we chose the example of a specific hurricane impacting a specific region, the mechanism is likely applicable to other climate-related events in other regions and other sectors. It is thus likely that the regional economic sectors that are best adapted to climate change gain significant advantage over their competitors under future warming.
Mapping the expansion of berry greenhouses onto Michoacán’s ejido lands, México
Authors: Hartman Sarah , Farfán Michelle , Hoogesteger Jaime , D’Odorico Paolo 
Published: October 2022

Abstract
Agricultural transformations have significantly contributed to the global market’s year-round supply of capital-intensive greenhouse-grown crops. For instance, berry production in México is increasingly relying on greenhouse systems to meet the growing demand of international markets, particularly in the USA. It is still unclear to what extent these transformations are related to land tenure, as data on greenhouse distribution often do not exist, are incomplete, or lack spatial resolution. This paper presents a support vector machine learning algorithm tool to map greenhouse expansion using satellite images. The tool is applied to the major berry-growing region of Michoacán, México. Here agricultural areas are transforming to satisfy foreign demand for berries, altering local land and water resource use patterns. We use this tool and a unique land tenure dataset to investigate (a) the spatially explicit extent to which high-input commercial agriculture (mainly the production of berries) has expanded in this region since 1989; and (b) the extent to which smallholder (ejidal) land has been incorporated into the highly capitalized agro-export sector. We combine a national dataset on ejidal land (which includes both communal and parcel land) with geospatial agricultural data to quantify the land-use changes in six municipalities in the berry-growing region of Michoacán between 1989 and 2021. We find that the development of the greenhouse berry boom can be quantified and shown with spatially-explicit detail, growing from zero to over 9,500 ha over the period, using almost one-quarter of all regional agricultural land in 2020. We further find that the capital-intensive market-oriented berry industry has been widely integrated into smallholder ejidal lands, so much so that over half of greenhouses are found there.
Agroforestry alters the fluxes of greenhouse gases of Moso bamboo plantation soil
Authors: Shi Man , Li Quan , Zhang Han , Sun Jilei , Zhang Junbo , Song Xinzhang 
Published: October 2022

Abstract
Agroforestry systems are widely applied in China and have both economic and ecological benefits. However, relatively few prior studies have investigated the relative ecological benefits of various agroforestry systems. In the present study, the static chamber method, quantitative polymerase chain reaction, high throughput sequencing were used to establish the differences in greenhouse gases (GHGs) fluxes and explore the bacterial and fungal populations affecting GHGs fluxes under different agroforestry systems, including pure Moso bamboo forest (CK), bamboo + Bletilla striata (BB), bamboo + Dictyophora indusiata (BD), and bamboo + chickens (BC). The highest cumulative CH4 uptake and N2O emission in spring occurred in BB while the highest cumulative CO2 emission and global warming potential (GWP) in spring occurred in BC. The Methylomirabilaceae were the key methanotrophs influencing the comparative differences in NO3
−associated CH4 uptake among the various agroforestry systems. N2O emission was associated with pH, and nitrifiers such as the ammonia-oxidizing archaea and bacteria (Nitrospiraceae and Nitrosomonadaceae) rather than denitrifiers may be the key microbes affecting N2O emission in different agroforestry systems. The bacteria Actinobacteriota and Fibrobacteres and the fungi Ascomycetes and Basidiomycota were the primary microbial taxa influencing CO2 emission. The lignin-decomposing Basidiomycota played more important roles in CO2 emission than the cellulose-decomposing fungi and bacteria under the various agroforestry systems. CO2 emission was positively correlated with NO3
− in the bacterial community and was negatively correlated with NO3
− in the fungal community, implying two C decomposition mechanisms caused by denitrification dominated in bacteria and those caused by microbial nitrogen mining dominated in fungi. The foregoing results suggested that bamboo + B. striata had comparatively higher ecological benefits as it is associated with low GWP and external C fixation. The present study provided valuable information for screening bamboo-based agroforestry systems with high ecological benefits. It also elucidated the microbial mechanism explaining the observed differences in GHGs fluxes between the various agroforestry systems.
Effectiveness of multi-physics numerical model in simulating accelerated corrosion with spatial and temporal non-uniformity
Authors: Shetty Shanmukha , Banerjee Sauvik , Tallur Siddharth , Desai Yogesh M 
Published: October 2022

Abstract
This study is motivated by the need to develop an efficient numerical model to simulate non-uniform interfacial degradation of reinforcing steel in concrete in an accelerated corrosion setup considering the influence of differential aeration, moisture and conductivity. In this study, a multi-physics finite element (FE) model is presented to simulate spatially and temporally non-uniform surface topography of corroding steel with rust layer, and eliminates the assumption of uniform mass loss and its linear variation with time as per available literature that uses classical approach of Faraday’s law. The model is validated experimentally with accelerated corrosion setup. Unlike previous studies, pore saturation (PS) is continuously monitored and its existing experimental correlations with conductivity and oxygen diffusivity are adopted so that the model can be extended to simulate natural corrosion to enhance the accuracy of service life predictions. These evaluations can be made completely nondestructive and in real-time eliminating the challenges in capturing the influence of environment by the use of alternative parameters such as relative humidity from real climate change predictions. The key findings from the investigation reveal that incorporating local environmental parameters measured in situ allows for the model to naturally evolve with anodic and cathodic locations on steel surface avoiding the need to assume predefined locations. It is envisioned that the developed multi-physics FE model can be used as a reliable substitute to accelerated corrosion experiment which is frequently used for durability studies of corroding reinforced concrete (RC) members. It is shown that the daily and cumulative mass loss evaluated from the degraded surface topography of the corroded rebar using the simulated model are in good agreement with those evaluated experimentally. Further, the maximum pit depth evaluated from the simulated surface is validated that has valuable applications in estimating degraded strength of corroding steel and service life of RC members.
Texture direction analysis of micro-topographies using fractal geometry
Authors: Siemens Stefan , Kästner Markus , Reithmeier Eduard 
Published: October 2022

Abstract
In recent years fractal geometry has been repeatedly shown to help describe and characterize micro-topographies. Important properties of micro-topographies include roughness or texture direction. Consequently, in this work, fractal geometry is investigated to determine texture direction. For this purpose, synthetic data and real height maps of different micro-topographies are evaluated using the fractal power spectrum density method. The results are compared with a manual determination of the texture direction and determining the texture direction according to ISO 25 178 using the S

td
parameter. The results show that the fractal method is more accurate than the currently standardized method. Another advantage is that secondary texture directions can be detected. Thus, the fractal method is well suited for characterizing micro-topographies and can complement existing parameters from ISO 25 178.
Do protests influence environmental attitudes? Evidence from Extinction Rebellion
Authors: Kountouris Yiannis , Williams Eleri 
Published: October 2022

Abstract
Protests are frequently used to raise public awareness of environmental challenges and increase support for pro-environmental behavior and policy. In this paper we examine the influence of protests on environmental attitudes, focusing on Extinction Rebellion’s April 2019 campaign of civil disobedience in the UK. Using individual-level survey data collected around the time of the protest, we exploit its exogeneity to the timing of survey response, to compare attitudes towards sustainable lifestyles, perceptions of own environmental impact, support for pro-environmental policy and behavior, and views about the severity and imminence of environmental crises, before and after the protest. There is evidence that the protest is related to lower probability of opposing pro-environmental behavior and policy, and lower willingness to pay a premium for environmentally friendly consumption. We do not find evidence that the protest alienated the public from sustainable lifestyles, influenced perceptions of personal environmental impact, or views about the imminence and severity of environmental crises. Results suggest the need for systematic study of the impact of environmental protests on the general public’s environmental attitudes and behaviors.
Anisotropic magnetic and transport properties of orthorhombic o-Pr2Co3Ge5
Authors: Kyrk Trent M , Kennedy Ellis R , Galeano-Cabral Jorge , Wei Kaya , McCandless Gregory T , Scott Mary C , Baumbach Ryan E , Chan Julia Y 
Published: October 2022

Abstract
The crystal structure, electron energy-loss spectroscopy (EELS), heat capacity, and anisotropic magnetic and resistivity measurements are reported for Sn flux grown single crystals of orthorhombic Pr2Co3Ge5 (U2Co3Si5-type, Ibam). Our findings show that o-Pr2Co3Ge5 hosts nearly trivalent Pr ions, as evidenced by EELS and fits to temperature dependent magnetic susceptibility measurements. Complex magnetic ordering with a partially spin-polarized state emerges near T
sp = 32 K, with a spin reconfiguration transition near T
M = 15 K. Heat capacity measurements show that the phase transitions appear as broad peaks in the vicinity of T
sp and T
M. The magnetic entropy further reveals that crystal electric field splitting lifts the Hund’s rule degeneracy at low temperatures. Taken together, these measurements show that Pr2Co3Ge5 is an environment for complex f state magnetism with potential strongly correlated electron states.
Systematic Review of In Vitro Antimicrobial Susceptibility Testing for Bacillus anthracis, 1947–2019
Authors: Maxson Tucker , Kongphet-Tran Thiphasone , Mongkolrattanothai Thitipong , Travis Tatiana , Hendricks Katherine , Parker Corinne , McLaughlin Heather P , Bugrysheva Julia , Ambrosio Frank , Michel Pierre , Cherney Blake , Lascols Christine , Sue David 
Published: October 2022

Abstract
Bacillus anthracis, the causative agent of anthrax, is a high-consequence bacterial pathogen that occurs naturally in many parts of the world and is considered an agent of biowarfare or bioterrorism. Understanding antimicrobial susceptibility profiles of B. anthracis isolates is foundational to treating naturally occurring outbreaks and to public health preparedness in the event of an intentional release. In this systematic review, we searched the peer-reviewed literature for all publications detailing antimicrobial susceptibility testing of B. anthracis. Within the set of discovered articles, we collated a subset of publications detailing susceptibility testing that followed standardized protocols for Food and Drug Administration–approved, commercially available antimicrobials. We analyzed the findings from the discovered articles, including the reported minimal inhibitory concentrations. Across the literature, most B. anthracis isolates were reported as susceptible to current first-line antimicrobials recommended for postexposure prophylaxis and treatment. The data presented for potential alternative antimicrobials will be of use if significant resistance to first-line antimicrobials arises, the strain is bioengineered, or first-line antimicrobials are not tolerated or available.
Welder’s Anthrax: A Tale of 2 Cases
Authors: Hendricks Katherine , Martines Roosecelis Brasil , Bielamowicz Hannah , Boyer Anne E , Long Stephen , Byers Paul , Stoddard Robyn A , Taylor Kathryn , Kolton Cari Beesley , Gallegos-Candela Maribel , Roberts Christine , DeLeon-Carnes Marlene , Salzer Johanna , Dawson Patrick , Brown Dannette , Templeton-LeBouf Lindsey , Maves Ryan C , Gulvik Chris , Lonsway David , Barr John R , Bower William A , Hoffmaster Alex 
Published: October 2022

Abstract
Bacillus anthracis has traditionally been considered the etiologic agent of anthrax. However, anthrax-like illness has been documented in welders and other metal workers infected with Bacillus cereus group spp. harboring pXO1 virulence genes that produce anthrax toxins. We present 2 recent cases of severe pneumonia in welders with B. cereus group infections and discuss potential risk factors for infection and treatment options, including antitoxin.
Risk Factors for Severe Cutaneous Anthrax in a Retrospective Case Series and Use of a Clinical Algorithm to Identify Likely Meningitis and Evaluate Treatment Outcomes, Kyrgyz Republic, 2005–2012
Authors: Kutmanova Ainura , Zholdoshev Saparbai , Roguski Katherine M , Sholpanbay uulu Melis , Person Marissa K , Cook Rachel , Bugrysheva Julia , Nadol Patrick , Buranchieva Aisuluu , Imanbaeva Lira , Dzhangazieva Ainura , Bower William A , Hendricks Katherine 
Published: October 2022

Abstract

Background
US Centers for Disease Control and Prevention guidelines currently recommend triple-therapy antimicrobial treatment for anthrax meningitis. In the Kyrgyz Republic, a country with endemic anthrax, cutaneous anthrax patients are routinely hospitalized and treated successfully with only monotherapy or dual therapy. Clinical algorithms have been developed to identify patients with likely anthrax meningitis based on signs and symptoms alone. We sought to retrospectively identify likely meningitis patients in the Kyrgyz Republic using a clinical algorithm and evaluate risk factors and their outcomes by type of treatment.

Methods
We conducted a retrospective chart review of cutaneous anthrax patients in the Kyrgyz Republic from 2005 through 2012. Using previous methods, we developed a highly specific algorithm to categorize patients by meningitis status. We then evaluated patient risk factors, treatments, and outcomes by disease severity and meningitis status.

Results
We categorized 37 of 230 cutaneous anthrax patients as likely having meningitis. All 37 likely meningitis patients survived, receiving only mono- or dual-therapy antimicrobials. We identified underlying medical conditions, such as obesity, hypertension, and chronic obstructive pulmonary disease, and tobacco and alcohol use, as potential risk factors for severe anthrax and anthrax meningitis.

Conclusions
Based on our analyses, treatment of anthrax meningitis may not require 3 antimicrobials, which could impact future anthrax treatment recommendations. In addition, chronic comorbidities may increase risk for severe anthrax and anthrax meningitis. Future research should further investigate potential risk factors for severe anthrax and their impact on laboratory-confirmed meningitis and evaluate mono- and dual-therapy antimicrobial regimens for anthrax meningitis.
Algorithms for the Identification of Anthrax Meningitis During a Mass Casualty Event Based on a Systematic Review of Systemic Anthrax From 1880 Through 2018
Authors: Binney Sophie , Person Marissa K , Traxler Rita M , Cook Rachel , Bower William A , Hendricks Katherine 
Published: October 2022

Abstract

Background
During an anthrax mass casualty event, prompt identification of patients with anthrax meningitis is important. Previous research has suggested use of a screening tool based on neurological symptoms and signs.

Methods
Using historical anthrax patient data from 1880 through 2018, we analyzed risk factors for meningitis. We developed lists of symptoms and signs (ie, algorithms) for predicting meningitis with high sensitivity and specificity. We evaluated both single and paired algorithms as screening tools.

Results
A single algorithm with 1 or more neurological symptoms or signs identifying patients with likely meningitis achieved high sensitivity (86%; 95% confidence interval [CI], 71%–100%) and specificity (90%; 95% CI, 82%–98%). Pairing algorithms with the same symptoms and signs (severe headache, altered mental status, meningeal signs, and “other neurological deficits”) improved specificity (99%; 95% CI, 97%–100%) but left 17.3% of patients in a middle “indeterminate” meningitis category and in need of additional diagnostic testing to determine likely meningitis status. Pairing algorithms with differing symptoms and signs also improved specificity over the single algorithm (92%; 95% CI, 85%–99%) but categorized just 2.5% of patients as indeterminate.

Conclusions
Our study confirms prior research suggesting quick and reliable assessment of patients for anthrax meningitis is possible based on the presence or absence of certain symptoms and signs. A single algorithm was adequate; however, if we assumed low-resource diagnostic testing was feasible for some patients, pairing algorithms improved specificity. Pairing algorithms with differing symptoms and signs minimized the proportion of patients requiring additional diagnostics.
Genome report: chromosome-level draft assemblies of the snow leopard, African leopard, and tiger (Panthera uncia, Panthera pardus pardus, and Panthera tigris)
Authors: Armstrong Ellie E , Campana Michael G , Solari Katherine A , Morgan Simon R , Ryder Oliver A , Naude Vincent N , Samelius Gustaf , Sharma Koustubh , Hadly Elizabeth A , Petrov Dmitri A 
Published: October 2022

Abstract
The big cats (genus Panthera) represent some of the most popular and charismatic species on the planet. Although some reference genomes are available for this clade, few are at the chromosome level, inhibiting high-resolution genomic studies. We assembled genomes from 3 members of the genus, the tiger (Panthera tigris), the snow leopard (Panthera uncia), and the African leopard (Panthera pardus pardus), at chromosome or near-chromosome level. We used a combination of short- and long-read technologies, as well as proximity ligation data from Hi-C technology, to achieve high continuity and contiguity for each individual. We hope that these genomes will aid in further evolutionary and conservation research of this iconic group of mammals.
CORAL: A framework for rigorous self-validated data modeling and integrative, reproducible data analysis
Authors: Novichkov Pavel S , Chandonia John-Marc , Arkin Adam P 
Published: October 2022

Abstract

Background
Many organizations face challenges in managing and analyzing data, especially when relevant datasets arise from multiple sources and methods. Analyzing heterogeneous datasets and additional derived data requires rigorous tracking of their interrelationships and provenance. This task has long been a Grand Challenge of data science and has more recently been formalized in the FAIR principles: that all data objects be Findable, Accessible, Interoperable, and Reusable, both for machines and for people. Adherence to these principles is necessary for proper stewardship of information, for testing regulatory compliance, for measuring the efficiency of processes, and for facilitating reuse of data-analytical frameworks.

Findings
We present the Contextual Ontology-based Repository Analysis Library (CORAL), a platform that greatly facilitates adherence to all 4 of the FAIR principles, including the especially difficult challenge of making heterogeneous datasets Interoperable and Reusable across all parts of a large, long-lasting organization. To achieve this, CORAL's data model requires that data generators extensively document the context for all data, and our tools maintain that context throughout the entire analysis pipeline. CORAL also features a web interface for data generators to upload and explore data, as well as a Jupyter notebook interface for data analysts, both backed by a common API.

Conclusions
CORAL enables organizations to build FAIR data types on the fly as they are needed, avoiding the expense of bespoke data modeling. CORAL provides a uniquely powerful platform to enable integrative cross-dataset analyses, generating deeper insights than are possible using traditional analysis tools.