bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changing the narrative: A Tool on African Traditions and the Preservation of Humanity during War
Authors: Mabeza Sarah Jean , Bolus Tamalin 
Published: May 2022

AbstractIn an effort towards better explaining the authority of international humanitarian law (IHL) on the African continent, the Regional Delegation of the International Committee of the Red Cross (ICRC) in Pretoria recently examined the relationship between African traditional customs and modern-day principles of IHL. Evidence of a clear correlation would illustrate a respect for the law of war on the African continent. The outcome of the research conducted by the ICRC was the creation of the “Tool on African Traditions and the Preservation of Humanity during War”, which illustrates eleven African traditions and the related principles of contemporary IHL. The Tool is a living project, which will continue to be updated, and which is presented in various formats that can be used for both pedagogical and operational outreach.
The importance of species selection in cover crop mixture design
Authors: McKenzie-Gopsill Andrew , Mills Aaron , MacDonald Ashley Nicolle , Wyand Sylvia 
Published: May 2022

AbstractCover crops are increasingly being included in crop rotations as a mechanism to promote diversity and provide agroecosystem services, including weed suppression. Recently, cover crop mixtures have increased in popularity in an attempt to provide a greater diversity in ecological services as compared with monocultures. Several recent studies, however, have failed to detect a positive effect of cover crop diversity on biomass production or weed suppression. Here we assessed biomass productivity and weed suppression in 19 cover crops seeded as monocultures and 19 mixtures of varying species composition and functional richness (two- and three-species mixtures) of full-season cover crops in Atlantic Canada. Cover crop biomass production and weed suppression varied by species identity, functional diversity, and species richness. As cover crop biomass increased regardless of diversity, weed biomass declined. Highly productive forbs and grasses provided the greatest weed suppression in monoculture. In line with previous observations, mixtures were not more productive or weed suppressive on average than the most productive monocultures. We observed that the inclusion of the highly productive species buckwheat (Fagopyrum esculentum Moench) and sorghum–sudangrass [Sorghum × drummondi (Nees ex Steud.) Millsp. & Chase] in a mixture increased stand evenness, productivity, weed suppression, and spatiotemporal stability. Taken together, our results suggest that effects of diversity on mixture productivity and weed suppression are species specific. This further demonstrates the importance of species selection in cover crop mixture design.
Belastungen, positive Veränderungen und Ressourcen von Familien in der COVID-19-Pandemie
Authors: Engelke Lara , Calvano Claudia , Klingbeil Karoline , Rolle Mira , Winter Sibylle M. , Renneberg und Babette 
Published: May 2022

Zusammenfassung. Theoretischer Hintergrund: Die Maßnahmen zur Eindämmung der COVID-19-Pandemie stellten Familien vor Herausforderungen. Es fehlt an Studien, welche die umfassende Vielfalt der subjektiven Erfahrungen abbilden. Fragestellung: Ziel ist, Belastungen, positive Veränderungen und Ressourcen in Familien zu erfassen. Methode: 4 967 Eltern (87.6 % weiblich, 86.7 % mit Hochschulreife) minderjähriger Kinder (0 – 17 Jahre) nahmen an einer Online-Erhebung im August 2020 teil. Belastungen, positive Veränderungen und Ressourcen während der Pandemie wurden durch offene Fragen erfasst. Auf Basis der Freitextantworten wurde ein Kategoriensystem entwickelt und ausgewertet. Ergebnisse: Die Vereinbarkeit von Beruf und Privatleben (12 %), Sorgen um die Entwicklung der Pandemie (11 %) und eingeschränkte Betreuung und schulische Bildung (9 %) wurden am häufigsten als Belastungen genannt. Positive Veränderungen waren vermehrte Wertschätzung, Dankbarkeit und neue Einstellungen (16 %), engere Beziehungen innerhalb der Familie (13 %) und mehr Zeit mit Menschen (11 %). Wichtige Ressourcen für Familien waren das soziale Miteinander innerhalb der Familie (19 %) und positive Aktivitäten (13 %). Diskussion und Schlussfolgerung: Ansatzpunkte für familienzentrierte Präventionsmaßnahmen sind die Offenhaltung von Betreuungseinrichtungen, eine Flexibilisierung der Arbeitssituation, eine fortlaufende Aufklärung über notwendige Maßnahmen, Stärkung digitaler Unterstützungsangebote einschließlich der Verbesserung der Medienkompetenz, die Ermöglichung von Freizeitaktivitäten, sowie die Verbesserung psychosozialer Unterstützungsmaßnahmen.
Impacts of Fine Particulate Matter From Wildfire Smoke on Respiratory and Cardiovascular Health in California
Authors: Heaney Alexandra , Stowell Jennifer D. , Liu Jia Coco , Basu Rupa , Marlier Miriam , Kinney Patrick 
Published: May 2022

AbstractIncreases in wildfire activity across the Western US pose a significant public health threat. While there is evidence that wildfire smoke is detrimental for respiratory health, the impacts on cardiovascular health remain unclear. This study evaluates the association between fine particulate matter (PM2.5) from wildfire smoke and unscheduled cardiorespiratory hospital visits in California during the 2004–2009 wildfire seasons. We estimate daily mean wildfire‐specific PM2.5 with Goddard Earth Observing System‐Chem, a global three‐dimensional model of atmospheric chemistry, with wildfire emissions estimates from the Global Fire Emissions Database. We defined a “smoke event day” as cumulative 0‐1‐day lag wildfire‐specific PM2.5 ≥ 98th percentile of cumulative 0–1 lag day wildfire PM2.5. Associations between exposure and outcomes are estimated using negative binomial regression. Results indicate that smoke event days are associated with a 3.3% (95% CI: [0.4%, 6.3%]) increase in visits for all respiratory diseases and a 10.3% (95% CI: [2.3%, 19.0%]) increase for asthma specifically. Stratifying by age, we found the largest effect for asthma among children ages 0–5 years. We observed no significant association between exposure and overall cardiovascular disease, but stratified analyses revealed increases in visits for all cardiovascular, ischemic heart disease, and heart failure among non‐Hispanic white individuals and those older than 65 years. Further, we found a significant interaction between smoke event days and daily average temperature for all cardiovascular disease visits, suggesting that days with high wildfire PM2.5 concentrations and high temperatures may pose greater risk for cardiovascular disease. These results suggest substantial increases in adverse outcomes from wildfire smoke exposure and indicate the need for improved prevention strategies and adaptations to protect vulnerable populations.
Limitations of Separate Cloud and Rain Categories in Parameterizing Collision‐Coalescence for Bulk Microphysics Schemes
Authors: Igel A. L. , Morrison H. , Santos S. P. , van Lier‐Walqui M. 
Published: May 2022

AbstractWarm rain collision‐coalescence has been persistently difficult to parameterize in bulk microphysics schemes. We use a flexible bulk microphysics scheme with bin scheme process parameterizations, called AMP, to investigate reasons for the difficulty. AMP is configured in a variety of ways to mimic bulk schemes and is compared to simulations with the bin scheme upon which AMP is built. We find that an important limitation in traditional bulk schemes is the use of separate cloud and rain categories. When the drop size distribution is instead represented by a continuous distribution, the simulation of cloud‐to‐rain conversion is substantially improved. We also find large sensitivity to the threshold size to distinguish cloud and rain in traditional schemes; substantial improvement is found by decreasing the threshold from 40 to 25 μm. Neither the use of an assumed functional form for the size distribution nor the choice of predicted distribution moments has a large impact on the ability of AMP to simulate rain production. When predicting four total moments of the liquid drop size distribution, either with a traditional two‐category, two‐moment scheme with a reduced size threshold, or a four‐moment single‐category scheme, errors in the evolution of mass and the cloud size distribution are similar, but the single‐category scheme has a substantially better representation of the rain size distribution. Optimal moment combinations for the single‐category approach are investigated and appear to be linked more to the information content they provide for constraining the size distributions than to their correlation with collision‐coalescence rates.
A greyscale erosion algorithm for tomography (GREAT) to rapidly detect battery particle defects
Authors: Wade A. , Heenan T. M. M. , Kok M. , Tranter T. , Leach A. , Tan C. , Jervis R. , Brett D. J. L. , Shearing P. R. 
Published: May 2022

AbstractParticle micro-cracking is a major source of performance loss within lithium-ion batteries, however early detection before full particle fracture is highly challenging, requiring time consuming high-resolution imaging with poor statistics. Here, various electrochemical cycling (e.g., voltage cut-off, cycle number, C-rate) has been conducted to study the degradation of Ni-rich NMC811 (LiNi0.8Mn0.1Co0.1O2) cathodes characterized using laboratory X-ray micro-computed tomography. An algorithm has been developed that calculates inter- and intra-particle density variations to produce integrity measurements for each secondary particle, individually. Hundreds of data points have been produced per electrochemical history from a relatively short period of characterization (ca. 1400 particles per day), an order of magnitude throughput improvement compared to conventional nano-scale analysis (ca. 130 particles per day). The particle integrity approximations correlated well with electrochemical capacity losses suggesting that the proposed algorithm permits the rapid detection of sub-particle defects with superior materials statistics not possible with conventional analysis.
The Great Dimming of Betelgeuse seen by the Himawari-8 meteorological satellite
Authors: Taniguchi Daisuke , Yamazaki Kazuya , Uno Shinsuke 
Published: May 2022

AbstractBetelgeuse, one of the most studied red supergiant stars1,2, dimmed in the optical range by ~1.2 mag between late 2019 and early 2020, reaching a historical minimum3–5 called ‘the Great Dimming’. Thanks to enormous observational effort to date, two hypotheses remain that can explain the Dimming1: a decrease in the effective temperature6,7 and an enhancement of the extinction caused by newly produced circumstellar dust8,9. However, the lack of multiwavelength monitoring observations, especially in the mid-infrared, where emission from circumstellar dust can be detected, has prevented us from closely examining these hypotheses. Here we present 4.5 yr, 16-band photometry of Betelgeuse between 2017 and 2021 in the 0.45–13.5 μm wavelength range making use of images taken by the Himawari-810 geostationary meteorological satellite. By examining the optical and near-infrared light curves, we show that both a decreased effective temperature and increased dust extinction may have contributed by almost equal amounts to the Great Dimming. Moreover, using the mid-infrared light curves, we find that the enhanced circumstellar extinction actually contributed to the Dimming. Thus, the Dimming event of Betelgeuse provides us with an opportunity to examine the mechanism responsible for the mass loss of red supergiants, which affects the fate of massive stars as supernovae11.
Association of Republican partisanship with US citizens’ mobility during the first period of the COVID crisis
Authors: Barbalat Guillaume , Franck Nicolas 
Published: May 2022

AbstractWhile Republican states have been criticized for their limited efforts to contain the spread of COVID-19, it is important to consider that political orientation can modify human behaviour via complex effects that are still poorly understood. During the first period of the pandemic, we found that the association of Republican partisanship with US citizens' mobility varied depending on the nature of the exposure being considered.
First, Republican partisanship was associated with increased mobility when the stringency of anti-COVID measures increased. Second, Republican partisanship was associated with decreased mobility when COVID-related deaths increased. Third, Republican partisanship was associated with increased mobility over time, i.e. as time went by, citizens living in Republican states were more mobile than those in Democratic states. These findings raise caution on any over-interpretation of the impact of polarization in US politics on COVID-related behaviour. They prompt consideration of persuasive tools that emphasize risk perception to promote social distancing in Republican states, rather than relying heavily on stringent anti-COVID interventions.
Estimation of milk yield based on udder measures of Pelibuey sheep using artificial neural networks
Authors: Angeles-Hernandez J. C. , Castro-Espinoza F. A. , Peláez-Acero A. , Salinas-Martinez J. A. , Chay-Canul A. J. , Vargas-Bello-Pérez E. 
Published: May 2022

AbstractUdder measures have been used to assess milk yield of sheep through classical methods of estimation. Artificial neural networks (ANN) can deal with complex non-linear relationships between input and output variables. In the current study, ANN were applied to udder measures from Pelibuey ewes to estimate their milk yield and this was compared with linear regression. A total of 357 milk yield records with its corresponding udder measures were used. A supervised learning was used to train and teach the network using a two-layer ANN with seven hidden structures. The globally convergent algorithm based on the resilient backpropagation was used to calculate ANN. Goodness of fit was evaluated using the mean square prediction error (MSPE), root MSPE (RMSPE), correlation coefficient (r), Bayesian’s Information Criterion (BIC), Akaike’s Information Criterion (AIC) and accuracy. The 15–15 ANN architecture showed that the best predictive milk yield performance achieved an accuracy of 97.9% and the highest values of r2 (0.93), and the lowest values of MSPE (0.0023), RMSPE (0.04), AIC (− 2088.81) and BIC (− 2069.56). The study revealed that ANN is a powerful tool to estimate milk yield when udder measures are used as input variables and showed better goodness of fit in comparison with classical regression methods.
Bacterial etiology and mortality rate in community-acquired pneumonia, healthcare-associated pneumonia and hospital-acquired pneumonia in Thai university hospital
Authors: Poovieng Jaturon , Sakboonyarat Boonsub , Nasomsong Worapong 
Published: May 2022

AbstractPneumonia is caused by infection at the pulmonary parenchyma which constitutes a crucial risk factor for morbidity and mortality. We aimed to determine the mortality rate and its risk factors as well as etiology among inpatients with community-acquired pneumonia (CAP), hospital-acquired pneumonia (HAP) and healthcare-associated pneumonia (HCAP). A hospital-based retrospective cohort study was conducted in a university hospital located in Bangkok, Thailand. A total of 250 inpatients with pneumonia was included in the present study. The inhospital mortality rate was 1.25 (95% CI 0.99–1.56) per 100 person-days. The present study reported that overall pneumonia caused by gram-negative pathogens accounted for 60.5%. P. aeruginosa was a frequent gram-negative pathogen among these participants, especially among patients with HCAP and HAP. Adjusted hazard ratio (AHR) of inhospital mortality among patients with HAP was 1.75 (95% CI 1.01–3.03) times that of those among patients with CAP, while AHR for 28-day mortality among patients with HAP compared with those with CAP was 2.81 (95% CI 1.38–5.75). Individual risks factors including cardiomyopathy, active-smoker and insulin use were potential risk factors for mortality. Initial qSOFA and acid-based disturbance should be assessed to improve proper management and outcomes.
Structure of the glucosyltransferase domain of TcdA in complex with RhoA provides insights into substrate recognition
Authors: Chen Baohua , Liu Zheng , Perry Kay , Jin Rongsheng 
Published: May 2022

AbstractClostridioides difficile is one of the most common causes of antibiotic-associated diarrhea in developed countries. As key virulence factors of C. difficile, toxin A (TcdA) and toxin B (TcdB) act by glucosylating and inactivating Rho and Ras family small GTPases in host cells, which leads to actin cytoskeleton disruption, cell rounding, and ultimately cell death. Here we present the co-crystal structure of the glucosyltransferase domain (GTD) of TcdA in complex with its substrate human RhoA at 2.60-angstrom resolution. This structure reveals that TcdA GTD grips RhoA mainly through its switch I and switch II regions, which is complemented by interactions involving RhoA’s pre-switch I region. Comprehensive structural comparisons between the TcdA GTD–RhoA complex and the structures of TcdB GTD in complex with Cdc42 and R-Ras reveal both the conserved and divergent features of these two toxins in terms of substrate recognition. Taken together, these findings establish the structural basis for TcdA recognition of small GTPases and advance our understanding of the substrates selectivity of large clostridial toxins.
Optimization of physical quantities in the autoencoder latent space
Authors: Park S. M. , Yoon H. G. , Lee D. B. , Choi J. W. , Kwon H. Y. , Won C. 
Published: May 2022

AbstractWe propose a strategy for optimizing physical quantities based on exploring in the latent space of a variational autoencoder (VAE). We train a VAE model using various spin configurations formed on a two-dimensional chiral magnetic system. Three optimization algorithms are used to explore the latent space of the trained VAE. The first algorithm, the single-code modification algorithm, is designed for improving the local energetic stability of spin configurations to generate physically plausible spin states. The other two algorithms, the genetic algorithm and the stochastic algorithm, aim to optimize the global physical quantities, such as topological index, magnetization, energy, and directional correlation. The advantage of our method is that various optimization algorithms can be applied in the latent space containing the abstracted representation constructed by the trained VAE model. Our method based on latent space exploration is utilized for efficient physical quantity optimization.
Increased MIB-1 expression in salivary gland pleomorphic adenoma that recurs and undergoes malignant transformation
Authors: Markkanen Anttoni , Aro Katri , Laury Anna Ray , Mäkitie Antti A. , Haglund Caj , Atula Timo , Hagström Jaana 
Published: May 2022

AbstractThe objective of this retrospective study was to explore possible changes in histopathological features and expression of cyclin D1 and MIB-1 in salivary gland pleomorphic adenomas (PAs) that recur or undergo malignant transformation. Knowledge of these characteristics might help to guide the management of these rare tumors. The histopathology and immunohistochemical staining characteristics of such tumors were analyzed in a cohort of 65 patients constituting three different groups of tumors: PA, recurrent pleomorphic adenoma (RPA) and carcinoma ex PA (CxPA). The RPAs were divided into two subgroups: primary PA that were known to recur later (PA-prim) and recurrent tumors appearing after a primary tumor (PA-rec). RPAs and CxPAs were compared with PAs without recurrence, which served as a control group. In our study, CxPA and PA-rec, but not PA-prim, showed increased MIB-1 expression compared with the control group. Neither cyclin D1 expression nor any histopathological features showed any association in statistical analyses. CxPA showed increased mitotic activity, squamous metaplasia, and nuclear atypia. Tumor multifocality was more frequent in PA-rec and CxPA. The different MIB-1 expression in CxPA and PA-rec in comparison to PA-prim suggests that the changes in expression could develop after the primary tumor.
Functional mimicry of Ruffini receptors with fibre Bragg gratings and deep neural networks enables a bio-inspired large-area tactile-sensitive skin
Authors: Massari Luca , Fransvea Giulia , D’Abbraccio Jessica , Filosa Mariangela , Terruso Giuseppe , Aliperta Andrea , D’Alesio Giacomo , Zaltieri Martina , Schena Emiliano , Palermo Eduardo , Sinibaldi Edoardo , Oddo Calogero Maria 
Published: May 2022

AbstractCollaborative robots are expected to physically interact with humans in daily living and the workplace, including industrial and healthcare settings. A key related enabling technology is tactile sensing, which currently requires addressing the outstanding scientific challenge to simultaneously detect contact location and intensity by means of soft conformable artificial skins adapting over large areas to the complex curved geometries of robot embodiments. In this work, the development of a large-area sensitive soft skin with a curved geometry is presented, allowing for robot total-body coverage through modular patches. The biomimetic skin consists of a soft polymeric matrix, resembling a human forearm, embedded with photonic fibre Bragg grating transducers, which partially mimics Ruffini mechanoreceptor functionality with diffuse, overlapping receptive fields. A convolutional neural network deep learning algorithm and a multigrid neuron integration process were implemented to decode the fibre Bragg grating sensor outputs for inference of contact force magnitude and localization through the skin surface. Results of 35 mN (interquartile range 56 mN) and 3.2 mm (interquartile range 2.3 mm) median errors were achieved for force and localization predictions, respectively. Demonstrations with an anthropomorphic arm pave the way towards artificial intelligence based integrated skins enabling safe human–robot cooperation via machine intelligence.
Meal delivery routing optimization with order allocation strategy based on transfer stations for instant logistics services
Authors: Li Jiulin , Yang Senyan , Pan Wenbo , Xu Ziwen , Wei Bo 
Published: May 2022

AbstractThe rapid development of instant logistics services has brought not only convenience to people's life but also a great challenge to traffic management. Due to the limited delivery range of instant delivery systems, customers are usually recommended the meals nearby or pay much higher delivery fees for long‐distance delivery. This study proposes a novel order splitting strategy based on transfer stations for long‐distance meal orders to satisfy the diverse customer demands. The meal delivery routing problem is addressed with an order allocation strategy based on transfer stations through developing a three‐stage modelling framework consisting of order combination, splitting and delivery routing for the online‐to‐offline instant logistics services. Normal meal orders are combined by the DBSCAN algorithm, and the cross‐regional long‐distance orders are split by transfer stations. Based on order combination and splitting, a mixed integer programming model is constructed for the meal delivery routing problem and solved by the adaptive large neighbourhood search algorithm. The proposed algorithm converges quickly for the tested instances constructed based on real platform data. The proposed order allocation strategy can expand the delivery scopes of couriers effectively, stimulate more potential orders and guarantee the timeliness of meal delivery.