bluuebunny/crossref_metadata_2025_split huggingface dataset:
Behavior of a Composite Steel Decking and Boarding System in Fire Based on Large-Scale Experimental Testing and Numerical Modelling
Authors: Claasen Jaleel , Cicione Antonio , Streicher Dirk , Walls Richard 
Published: June 2023

AbstractThis paper presents experimental and numerical results of an investigation into the thermal and structural behaviour of an innovative modular structural steel system, which includes cellular beams, that was tested in a 1-h standard fire scenario while loaded. The modular system consists of a 5.66 × 3.8 m rectangular steel frame, with a profiled steel sandwich decking (SD) system attached, which comprises of (a) profiled steel decking, (b) fibre cement, and (c) calcium silicate boards and strips. The SD system is suspended from the underside of the horizontal structural members to provide inherent fire protection to the steel beams from the bottom and acts as the load-bearing component of the flooring. The purpose of the experiment was to determine the fire resistance of the structural system, whilst under load, which is primarily based on the fire resistance of the SD system. Temperature data for the SD system was collected during the experiment and used to validate a numerical finite element analysis model. This study shows that the SD system was able to achieve a fire resistance rating of 57 min in the experiment which was governed by insulation resistance. A lower fire resistance rating is estimated based on numerical models. Structural resistance was maintained throughout the test. During preliminary testing structural collapse was observed in a separate experiment which highlights how the system is sensitive to damage to the ceiling boards. Numerical results highlight that thermal bowing and movement may result in changes in thermal interactions between adjacent elements. This paper provides novel large-scale experimental data on a loaded flooring system in fire.
Efficient Key Generation Techniques for Wireless Body Area Network
Authors: Divya S. , Prema K. V. , Muniyal Balachandra 
Published: June 2023

AbstractIn wireless body area network health care applications, energy-constraint wearable devices are used to monitor patient physiological parameters. The security of the private health information of a person plays a significant role because if it is captured and read by an unauthorized person, the confidentiality of the patient data is lost. Therefore, there is a requirement to secure the data by performing encryption to transfer it into an unreadable form. Since the resources used for encryption should be kept to a minimum as the devices are attached to the human body, a lightweight encryption algorithm has to be used. Therefore, the generation of a unique key used for encryption plays a significant role. In work, generating a unique key uses the ECG values taken from MIT-BIH Arrhythmia database. Four unique keys are generated, which can be used for encryption. The uniqueness and randomness of the keys generated are proved using the runs test and frequency test within the block. Also, the average hamming distance calculated between the ECG keys generated from two different ECG signals is 62.5% ($$\approx$$
≈
80 bits), which proves the distinctiveness of the keys generated. Implementation of the work is performed using Matlab.
Combining historical aerial photography with machine learning to map landscape change impacts on dry grasslands in the Central Alps
Authors: Kindermann Elisabeth , Hölzel Norbert , Wellstein Camilla 
Published: June 2023

Abstract
Context
Striking land-use changes after WW II characterize the past century in the European Alps with impact on ecosystems and biodiversity. Documenting land-use changes is often difficult due to limited information from the past. Mapping landscape history with aerial photography can foster the understanding of human-induced changes in vulnerable ecosystems, such as the remnants of dry grasslands in the Central Alps.

Objectives
We aimed to assess changes in grassland vegetation and their current extent in Val Venosta (European Alps, Italy) in relation to overall landscape settings, anthropogenic drivers of change and the effectiveness of the protected areas.

Methods
We performed a land-cover classification based on a mixed machine learning approach including several auxiliary classifiers in a random forest model to characterise the extent and state of (dry) grasslands. We calculated landscape metrics between 1945 and 2015 to assess shape-related changes, especially regarding their landscape embedding and the protection status of sites.

Results
Three main processes related to a changing extent in grassland habitat prevail: (i) agricultural intensification, (ii) settlement expansion at the valley bottom and (iii) forest expansion (afforestation and encroachment due to decreasing pasture activities) on the valley slopes. The remaining grassland habitat is increasingly isolated and fragmented, leaving only few core areas of dry grassland, which tended to be better conserved within protected areas.

Conclusion
The changes in extent of dry grasslands revealed marked changes. Transformations are assumed to be predominantly caused by human impact and successional changes. Our results confirm the importance of protected area networks. The pronounced landscape changes underline the urgent need for future research with explicit focus on the changes at community level and the underlying causes. Identifying all relevant drivers of change should be a key element in targeted conservation efforts.
In situ electron microscopy techniques for nanoparticle dispersion analysis of commercial sunscreen
Authors: Ilett M. , Naveed E. , Roncal-Herrero T. , Aslam Z. , Micklethwaite S. , Hondow N. 
Published: June 2023

AbstractNanoparticles are common active ingredients within many commercial products including sunscreen. Consequently, accurate characterisation of nanoparticles in these products is vital to enhance product design, whilst also understanding the toxicological implications of these nanoparticles. Whilst bulk techniques are useful in providing some information, they often cannot resolve individual particles, and therefore electron microscopy can be used for high-resolution nanoparticle characterisation. However, conventional high vacuum dry TEM does not accurately represent nanoparticle dispersions and other in situ methods must be used. Here, we use a combination of techniques including liquid cell transmission electron microscopy (LCTEM), cryogenic (cryo)-TEM and cryo-scanning electron microscopy (SEM) to characterise a commercial sunscreen containing titanium dioxide (TiO2) and zinc oxide (ZnO) nanoparticles. Our work illustrates that whilst LCTEM does not require any sample preparation more beam artefacts can occur causing ZnO dissolution with only TiO2 nanoparticles visualised. Comparatively, cryo-TEM allows characterisation of both ZnO and TiO2, yet only cryo-SEM could be used to analyse the pure product (without dilution) but biased the characterisation to the larger fraction of nanoparticles and agglomerates. Ultimately, only with a combination of different in situ EM techniques can an accurate characterisation of commercial products be achieved in order to ensure effective and safe product design and manufacture.
Computing corporate bond returns: a word (or two) of caution
Authors: Andreani Martina , Palhares Diogo , Richardson Scott 
Published: June 2023

AbstractWe offer several suggestions for researchers using corporate bond return data. First, despite clear instructions from older papers (e.g., Bessembinder et al., The Review of Financial Studies 22:4219–4258, 2009) about ways to compute credit excess returns, a lot of recent research simply subtracts a Treasury Bill return. We show that this imprecision is likely to contaminate inferences, as the rate component of returns is negatively correlated to the spread component. This is a problem for all research looking at corporate bond returns, especially time series analysis and safer corporate bonds (e.g., investment grade). We provide a simple approach using Wharton Research Data Services (WRDS) data to remove the interest rate component of corporate bond returns. Second, we note significant differences in the coverage of corporate bonds across the Trade Reporting and Compliance Engine (TRACE) platform and typical corporate bond indices. We provide some simple rules for researchers who are using TRACE to select a subset of bonds closest to those contained inside corporate bond indices used by institutional investors. Third, we note differential quality in the prices and hence returns between TRACE and typical corporate bond indices. Corporate bond returns provided by corporate bond indices (i) correctly estimate credit excess returns, (ii) are synchronous for the entire set of bonds, allowing for consistent cross-sectional comparability, and (iii) suffer less from stale pricing issues. Due to these coverage and data quality issues, researchers should try, where possible, to source return data from multiple sources to ensure the robustness of their results.
GEnZ explorer: a tool for visualizing agroclimate to inform research and regulatory risk assessment
Authors: Melnick Rachel L. , Jarvis Larissa , Hendley Paul , Garcia-Alonso Monica , Metzger Marc J. , Ramankutty Navin , Teem John L. , Roberts Andrew 
Published: June 2023

AbstractConfined field trials (CFT) of genetically engineered (GE) crops are used to generate data to inform environmental risk assessments (ERA). ERAs are required by regulatory authorities before novel GE crops can be released for cultivation. The transportability of CFT data to inform risk assessment in countries other than those where the CFT was conducted has been discussed previously in an analysis showing that the primary difference between CFT locations potentially impacting trial outcomes is the physical environment, particularly the agroclimate. This means that data from trials carried out in similar agroclimates could be considered relevant and sufficient to satisfy regulatory requirements for CFT data, irrespective of the country where the CFTs are conducted. This paper describes the development of an open-source tool to assist in determining the transportability of CFT data. This tool provides agroclimate together with overall crop production information to assist regulators and applicants in making informed choices on whether data from previous CFTs can inform an environmental risk assessment in a new country, as well as help developers determine optimal locations for planning future CFTs. The GEnZ Explorer is a freely available, thoroughly documented, and open-source tool that allows users to identify the agroclimate zones that are relevant for the production of 21 major crops and crop categories or to determine the agroclimatic zone at a specific location. This tool will help provide additional scientific justification for CFT data transportability, along with spatial visualization, to help ensure regulatory transparency.
Environmental heterogeneity affecting spatial distribution of phytoplankton community structure and functional groups in a large eutrophic lake, Lake Chaohu, China
Authors: Cao Huijuan , Zhang Kun , Deng Daogui , Qi Huiying , Li Jun , Cao Yaqin , Jin Qide , Zhao Yajie , Wang Yeping , Wu Zhou , Li Xinyue , Li Ying 
Published: June 2023

AbstractThe growth and development of phytoplankton are influenced by physico-chemical parameters, which can also affect the spatial distribution of phytoplankton community structure. However, it is unclear whether environmental heterogeneity caused by multiple physico-chemical factors can affect the spatial distribution of phytoplankton and its functional groups. In this study, we investigated the seasonal variation and spatial distribution of phytoplankton community structure and its relationships with environmental factors in Lake Chaohu from August 2020 to July 2021. We recorded a total of 190 species from 8 phyla, which were divided into 30 functional groups, including 13 dominating functional groups. The average annual phytoplankton density and biomass were (5.46 ± 7.17) × 107 cells/L and 4.80 ± 4.61 mg/L, respectively. The density and biomass of phytoplankton were higher in summer ((14.64 ± 20.34) × 107 cells/L, 10.61 ± 13.16 mg/L) and autumn ((6.79 ± 3.97) × 107 cells/L, 5.57 ± 2.40 mg/L), with the M and H2 of dominant functional groups. The dominant functional groups were N, C, D, J, MP, H2, and M in spring, whereas functional groups C, N, T, and Y dominated in winter. The distribution of phytoplankton community structure and dominant functional groups exhibited significant spatial heterogeneity in the lake, which was consistent with the environmental heterogeneity of the lake and could be classified into four locations. Location I had higher phytoplankton density and biomass than the other three locations. Additionally, dominant functional groups M, C, and H2 were present throughout the lake, and all 13 dominant functional groups were observed in Location II. Our findings suggest that environmental heterogeneity is a key factor influencing the spatial distribution of phytoplankton functional groups in Lake Chaohu.
Die Anwendung der Propensity-Score-Methode
Authors: Matteucci Gothe Raffaella 
Published: June 2023

Zusammenfassung
Hintergrund
Bei der Ermittlung von Behandlungseffekten mit Real World Data (RWD) kann die Gefahr bestehen, verzerrte Ergebnisse zu erhalten, wenn die Verteilung der Vorbehandlungscharakteristika der Studienteilnehmer in den zu vergleichenden Gruppen unterschiedlich ist (Confounding). Propensity Scores (PS) sind eine geeignete Methode zur Bildung von Gruppen mit vergleichbarer Verteilung von Charakteristika, um anschließend den interessierenden Behandlungseffekt zu schätzen.

Ziel der Arbeit
Ziel des vorliegenden Beitrags ist eine Einführung in die Berechnung und Anwendung von PS.

Material und Methoden
Die Methode der PS wird beschrieben und mit Bezug zur Übersichtsliteratur erläutert. Vor- und Nachteile der Methodik werden aufgezeigt.

Ergebnisse
Es wird dargestellt, wie PS berechnet und angewendet werden. Varianten der Berechnung sind: die logistische oder die Probit-Regression, die Diskriminanzanalyse, „classification and regression trees“ (CART), neuronale Netze und andere Methoden. PS werden zum Matching, zur Stratifizierung, zur Gewichtung und im Rahmen einer Regression angewandt.

Schlussfolgerung
Die Anwendung der PS führt zu einem quasiexperimentellen Studiendesign und hilft ggf. unverzerrte Behandlungseffekte im Rahmen der Analyse von RWD zu schätzen.
Introducing the Intergovernmental Policy Output Dataset (IPOD)
Authors: Lundgren Magnus , Squatrito Theresa , Sommerer Thomas , Tallberg Jonas 
Published: June 2023

AbstractThere is a growing recognition that international organizations (IOs) formulate and adopt policy in a wide range of areas. IOs have emerged as key venues for states seeking joint solutions to contemporary challenges such as climate change or COVID-19, and to establish frameworks to bolster trade, development, security, and more. In this capacity, IOs produce both extraordinary and routine policy output with a multitude of purposes, ranging from policies of historic significance like admitting new members to the more mundane tasks of administering IO staff. This article introduces the Intergovernmental Policy Output Dataset (IPOD), which covers close to 37,000 individual policy acts of 13 multi-issue IOs in the 1980–2015 period. The dataset fills a gap in the growing body of literature on the comparative study of IOs, providing researchers with a fine-grained perspective on the structure of IO policy output and data for comparisons across time, policy areas, and organizations. This article describes the construction and coverage of the dataset and identifies key temporal and cross-sectional patterns revealed by the data. In a concise illustration of the dataset’s utility, we apply models of punctuated equilibria in a comparative study of the relationship between institutional features and broad policy agenda dynamics. Overall, the Intergovernmental Policy Output Dataset offers a unique resource for researchers to analyze IO policy output in a granular manner and to explore questions of responsiveness, performance, and legitimacy of IOs.
Effects of site productivity on individual tree maximum basal area growth rates of Eucalyptus pilularis in subtropical Australia
Authors: West P. W. 
Published: June 2023

AbstractInventory data were available from 96 plots of even-aged, monoculture, tall-open forests of Eucalyptus pilularis Smith, aged 2–63 years, growing in sub-tropical regions along the east coast of Australia. A model was developed relating the maximum possible stem basal area growth rate of individual trees to their stem basal area. For any tree size, this maximum increased as site productivity increased. However, the size at which this maximum occurred decreased as productivity increased. Much research has shown that, at any stand age, trees of a particular stem basal area are taller on more productive sites than on less productive ones. Taller trees incur greater respiratory costs to ensure maintenance of the photosynthetic capacity of their canopies; this reduces their growth rates. It was concluded that trees with larger basal areas will have the maximum possible growth rate on a less productive site, whilst trees with smaller basal areas will have the maximum possible on a more productive site. The model developed may constitute the first stage of a complete individual tree growth model system to predict wood yields from these forests.
Smart and sustainable scheduling of charging events for electric buses
Authors: Jarvis Padraigh , Climent Laura , Arbelaez Alejandro 
Published: June 2023

AbstractThis paper presents a framework for the efficient management of renewable energies to charge a fleet of electric buses (eBuses). Our framework starts with the prediction of clean energy time windows, i.e., periods of time when the production of clean energy exceeds the demand of the country. Then, the optimization phase schedules charging events to reduce the use of non-clean energy to recharge eBuses while passengers are embarking or disembarking. The proposed framework is capable of overcoming the unstable and chaotic nature of wind power generation to operate the fleet without perturbing the quality of service. Our extensive empirical validation with real instances from Ireland suggests that our solutions can significantly reduce non-clean energy consumed on large data sets.
Biological effects of particulate matter samples during the COVID-19 pandemic: a comparison with the pre-lockdown period in Northwest Italy
Authors: Gea Marta , Macrì Manuela , Marangon Daniele , Pitasi Francesco Antonio , Fontana Marco , Schilirò Tiziana , Bonetta Sara 
Published: June 2023

AbstractIn 2020, during the COVID-19 pandemic, containment measures were applied inducing potential changes in air pollutant concentrations and thus in air toxicity. This study evaluates the role of restrictions on biological effects of particulate matter (PM) in different Northwest Italy sites: urban background, urban traffic, rural, and incinerator. Daily PM samples collected in 2020 were pooled according to restrictions: January/February (no restrictions), March and April (first lockdown), May/June and July/August/September (low restrictions), October/November/December (second lockdown). The 2019 samples (pre-pandemic period) were pooled as 2020 for comparison. Pools were extracted with organic solvents and extracts were tested to assess cytotoxicity (WST-1 assay) and genotoxicity (comet assay) on BEAS-2B cells, mutagenicity (Ames test) on TA98 and TA100 Salmonella typhimurium strains, and estrogenic activity (gene reporter assay) on MELN cells. Pollutant concentrations were also analyzed (PM10, PM2.5, polycyclic aromatic hydrocarbons). No difference was observed for PM and polycyclic aromatic hydrocarbon concentrations between 2020 and 2019. During lockdown months (2020), PM cytotoxicity/genotoxicity was significantly lower in some sites than during 2019, while considering PM mutagenicity/estrogenic activity some differences were detected but without statistical significance. PM extract effects decreased in some sites during 2020; this may be due to lockdowns that reduced/modified pollutant emissions and may be related also to complex PM origin/formation and to meteorological conditions. In conclusion, the study confirms that PM biological effects cannot be assessed considering only the PM concentration and suggests to include a battery of bioassay for air quality monitoring in order to protect human health from air pollution effects.
Graphical Abstract
Direct Oral Anticoagulants for Cancer-Associated Venous Thromboembolism
Authors: Masini Marta , Toma Matteo , Spallarossa Paolo , Porto Italo , Ameri Pietro 
Published: June 2023

Abstract
Purpose of Review
To present the randomized controlled trial (RCT) evidence and highlight the areas of uncertainty regarding direct oral anticoagulants (DOAC) for cancer-associated venous thromboembolism (CAT).

Recent Findings
In the last years, four RCTs have shown that rivaroxaban, edoxaban, and apixaban are at least as effective as low-molecular-weight heparin (LMWH) for the treatment of both incidental and symptomatic CAT. On the other hand, these drugs increase the risk of major gastrointestinal bleeding in patients with cancer at this site. Another two RCTs have demonstrated that apixaban and rivaroxaban also prevent CAT in subjects at intermediate-to-high risk commencing chemotherapy, albeit at the price of higher likelihood of bleeding. By contrast, data are limited about the use DOAC in individuals with intracranial tumors or concomitant thrombocytopenia. It is also possible that some anticancer agents heighten the effects of DOAC via pharmacokinetic interactions, up to making their effectiveness-safety profile unfavorable.

Summary
Leveraging the results of the aforementioned RCTS, current guidelines recommend DOAC as the anticoagulants of choice for CAT treatment and, in selected cases, prevention. However, the benefit of DOAC is less defined in specific patient subgroups, in which the choice of DOAC over LMWH should be carefully pondered.
Circulating Acylcarnitines Associated with Hypertrophic Cardiomyopathy Severity: an Exploratory Cross-Sectional Study in MYBPC3 Founder Variant Carriers
Authors: Jansen Mark , Schmidt A. F. , Jans J. J. M. , Christiaans I. , van der Crabben S. N. , Hoedemaekers Y. M. , Dooijes D. , Jongbloed J. D. H. , Boven L. G. , Lekanne Deprez R. H. , Wilde A. A. M. , van der Velden J. , de Boer R. A. , van Tintelen J. P. , Asselbergs F. W. , Baas A. F. 
Published: June 2023

Abstract
Hypertrophic cardiomyopathy (HCM) is a relatively common genetic heart disease characterised by myocardial hypertrophy. HCM can cause outflow tract obstruction, sudden cardiac death and heart failure, but severity is highly variable. In this exploratory cross-sectional study, circulating acylcarnitines were assessed as potential biomarkers in 124 MYBPC3 founder variant carriers (59 with severe HCM, 26 with mild HCM and 39 phenotype-negative [G + P-]). Elastic net logistic regression identified eight acylcarnitines associated with HCM severity. C3, C4, C6-DC, C8:1, C16, C18 and C18:2 were significantly increased in severe HCM compared to G + P-, and C3, C6-DC, C8:1 and C18 in mild HCM compared to G + P-. In multivariable linear regression, C6-DC and C8:1 correlated to log-transformed maximum wall thickness (coefficient 5.01, p = 0.005 and coefficient 0.803, p = 0.007, respectively), and C6-DC to log-transformed ejection fraction (coefficient -2.50, p = 0.004). Acylcarnitines seem promising biomarkers for HCM severity, however prospective studies are required to determine their prognostic value.
Graphical abstract