bluuebunny/crossref_metadata_2025_split huggingface dataset:
The archbishop’s dinner? Late medieval fish from Esztergom-Várhegy-Kőbánya, Hungary
Authors: Bartosiewicz László , Gál Erika 
Published: July 2021

AbstractFourteenth–fifteenth century food refuse from the kitchen of the Esztergom archbishopric shows a significant diachronic increase in cyprinid bones, in particular those of carp. Meanwhile, contributions by large acipenserids and carnivorous species (catfish/wels, pike, percids) declined. Contemporaneous account books indirectly suggest that the archbishop’s kitchen must have increasingly relied on farmed carp fish. Sturgeons were a commodity sold by the archbishopric but rarely consumed. Expensive pikes were bought at low prices for the archbishop, possibly related to the small size of individuals found in the deposits. The poor representation of high-status fish is consonant with the scarcity of bones from large game in an assemblage dominated by domesticates. Wild game is represented by brown hare, partridge, and a variety of thrushes. These finds confirm that the foodways in the archbishop’s palace were more modest than expected on the basis of its social status. Increasing contributions by cyprinids and sterlet to the assemblage also coincide with the high relative frequency of their recipes in a sixteenth century cookbook.
Biophysical reviews top five: atomic force microscopy in biophysics
Authors: Ando Toshio 
Published: July 2021

AbstractSince its invention in the late 1980s, atomic force microscopy (AFM), in which a nanometer-sized tip is used to physically interrogate the properties of a surface at high resolution, has brought about scientific revolutions in both surface science and biological physics. In response to a request from the journal, I have prepared a top-five list of scientific papers that I feel represent truly landmark developments in the use of AFM in the biophysics field. This selection is necessarily limited by number (just five) and subjective (my opinion) and I offer my apologies to those not appearing in this list.
Mining Knowledge of Respiratory Rate Quantification and Abnormal Pattern Prediction
Authors: Szczuko Piotr , Kurowski Adam , Odya Piotr , Czyżewski Andrzej , Kostek Bożena , Graff Beata , Narkiewicz Krzysztof 
Published: July 2021

AbstractThe described application of granular computing is motivated because cardiovascular disease (CVD) remains a major killer globally. There is increasing evidence that abnormal respiratory patterns might contribute to the development and progression of CVD. Consequently, a method that would support a physician in respiratory pattern evaluation should be developed. Group decision-making, tri-way reasoning, and rough set–based analysis were applied to granular computing. Signal attributes and anthropomorphic parameters were explored to develop prediction models to determine the percentage contribution of periodic-like, intermediate, and normal breathing patterns in the analyzed signals. The proposed methodology was validated employing k-nearest neighbor (k-NN) and UMAP (uniform manifold approximation and projection). The presented approach applied to respiratory pattern evaluation shows that median accuracies in a considerable number of cases exceeded 0.75. Overall, parameters related to signal analysis are indicated as more important than anthropomorphic features. It was also found that obesity characterized by a high WHR (waist-to-hip ratio) and male sex were predisposing factors for the occurrence of periodic-like or intermediate patterns of respiration. It may be among the essential findings derived from this study. Based on classification measures, it may be observed that a physician may use such a methodology as a respiratory pattern evaluation-aided method.
Morphological Variability of Silica Polymorphs within Crustal Xenoliths from Tapi Dyke Swarm, Northern Deccan Traps and their Petrogenetic Significance
Authors: Bhardwaj Savyasachi , Monteiro Aristle , Bhoyar Chandrakant , Duraiswami Raymond A. 
Published: July 2021

Abstract
Crustal xenoliths, mostly of granite gneiss, occur within mafic dykes from Ranala, Rajmane-Talwade and Vadli from within the Tapi rift, northern Deccan Traps. Many xenoliths are highly brecciated, show mylonite textures and rare pseudotachylite streaks. Widespread occurrence of tridymite and cristobalite± sanidine is confirmed in xenoliths in thin sections, scanning electron micrographs and x-ray diffraction analyses. The silica polymorphs exhibit diverse morphologies. The xenoliths record widespread cataclastic metamorphism, and mineralogical phase transformations due to contact metamorphism at temperatures ranging from 1400 to &gt;1710 °C and pressures &lt;0.1 GPa corresponding to sanidinite hornfels facies. Xenolith-based present study provides explicit field and petrological evidences which supports geophysical signature of a highly fractured, sheared, and faulted Precambrian basement beneath the Tapi rift. Some of these tectonic features provided pathways for magmatic plumbing system (feeder dykes) related to the Deccan Trap volcanism.
Stability Assessment of Ukhrul-Jessami Road Cut Slopes, Ukhrul District, Manipur
Authors: Bidyashwari H. , Okendro M. , Kushwaha R.A.S. , Chandra M. 
Published: July 2021

Abstract
The present study is to assess the slope stability of road cuts along the National Highway 150 (202 present). Rock mass classification enables preliminary assessment of rock slope failure and guide the planners to choose suitable alignment for road construction and engineering structures. This technique includes collection of data from the intact rock and discontinuity parameters. Seven locations have been selected for slope stability analysis using RMR, SMR and CoSMR techniques. These empirical methods are used to determine the mode of failures and characterise the slope as well. Kinematic analysis deciphers the causes of instability and the mode of discontinuous rock failures. Results shows majority of road section between Ukhrul and Jessami falls under partial stable to unstable zone.
Dimensions of the ‘Body’ in Tranquility Meditation
Authors: Anālayo Bhikkhu 
Published: July 2021

AbstractA perusal of selected forms of early Buddhist tranquility meditation brings to light the complexity of the roles assumed by the Indic term kāya, usually translated as “body,” which corresponds to the domain of the first establishment of mindfulness. The present exploration of such complexity, which proceeds in critical dialogue with positions taken by Eviatar Shulman, covers the significance of the supernormal feat of conjuring up a mind-made body, the mindful contemplation of the somatic dimensions of absorption attainment, and the transition from these to the immaterial spheres. The patterns of early Buddhist thought that emerge in this way make it preferable to understand the compass of the term kāya to cover a continuum of somatic experiences that can range from gross materiality to more subtle types of embodiments. Even immaterial experiences, based on the complete transcendence of materiality, can still be conceptualized with the help of the term kāya in a phrase that serves to convey direct and personal experience.
Fano 3-folds from homogeneous vector bundles over Grassmannians
Authors: De Biase Lorenzo , Fatighenti Enrico , Tanturri Fabio 
Published: July 2021

AbstractWe rework the Mori–Mukai classification of Fano 3-folds, by describing each of the 105 families via biregular models as zero loci of general global sections of homogeneous vector bundles over products of Grassmannians.
The direct and interactive effects of elevated CO2 and additional nitrate on relative costs and benefits of legume-rhizobia symbiosis
Authors: Oono Ryoko , Ho Randy , Jimenez Salinas Andres 
Published: July 2021

AbstractRising concentrations of carbon dioxide (CO2) is likely to have important effects on growth and development of plants and on their relationship with symbiotic microbes. A rise in CO2 could increase demand by plant hosts for nutrient resources, which may increase host investments in beneficial symbionts. In the legume-rhizobia mutualism, while elevated CO2 is often associated with increased nodule growth and investment in N2-fixing rhizobia, it is yet unclear if this response depends on the mutualistic quality of the rhizobia. To test if host carbon allocation towards more-beneficial nodules are similar to less-beneficial (but still effective) nodules when plant N demand changes, we manipulated plant C and N status with elevated CO2 and additional nitrate. We used two isogenic Rhizobium etli strains that differ in their ability to synthesize an energy reserve compound, poly-beta-hydroxybutyrate (PHB), as well as their efficiencies for nitrogen fixation and nodulation rates, resulting in two Phaseolus vulgaris host groups with either large number of small nodules or small number of large nodules. The addition of nitrate negatively affected carbon allocation towards nodules, and elevated CO2 reversed this effect, as expected. However, this alleviation of nodule inhibition was greater on plants that started with greater numbers of smaller nodules. If smaller nodules indicate less-efficient or low-fixing rhizobia, this study suggests that increased demand for nitrogen in the face of elevated CO2 has the potential to disproportionately favor less-beneficial strains and increase variation of nitrogen fixation quality among rhizobia.
Diffusion dynamics of influence in a social network of intellectuals
Authors: Ghawi Raji , Petz Cindarella , Pfeffer Jürgen 
Published: July 2021

AbstractThe history of intellectuals consists of a complex web of influences and interconnections of philosophers, scientists, writers, their work, and ideas. To understand how did these influences evolve over time, we mined a network of influence of over 12,500 intellectuals, enriched it with a temporal dimension dividing the history into six eras. We analyze time-sliced projections of the network into within-era, inter-era, and accumulated-era networks, and identify various patterns of intellectuals and eras and studied their development in time. We also construct influence cascades, analyze their properties: size, depth and breadth, and analyze how the cascades of influence evolve over the consecutive eras. We find out that the cascades are clustered into two categories, namely small- and large cascades. An interesting finding here is that the fraction of small cascades increases, while the fraction of larges cascades decreases over time. We also briefly analyze the community structure within the influence network of scholars.
Holomorphic functions, relativistic sum, Blaschke products and superoscillations
Authors: Alpay Daniel , Colombo Fabrizio , Pinton Stefano , Sabadini Irene 
Published: July 2021

AbstractSuperoscillating functions are band-limited functions that can oscillate faster than their fastest Fourier component. The notion of superoscillation is a particular case of that one of supershift. In the recent years, superoscillating functions, that appear for example in weak values in quantum mechanics, have become an interesting and independent field of research in complex analysis and in the theory of infinite order differential operators. The aim of this paper is to study some infinite order differential operators acting on entire functions which naturally arise in the study of superoscillating functions. Such operators are of particular interest because they are associated with the relativistic sum of the velocities and with the Blaschke products. To show that some sequences of functions preserve the superoscillatory behavior it is of crucial importance to prove that their associated infinite order differential operators act continuously on some spaces of entire functions with growth conditions.
Up-Scalable Fabrication of SnO2 with Multifunctional Interface for High Performance Perovskite Solar Modules
Authors: Tong Guoqing , Ono Luis K. , Liu Yuqiang , Zhang Hui , Bu Tongle , Qi Yabing 
Published: July 2021

AbstractTin dioxide (SnO2) has been demonstrated as one of the promising electron transport layers for high-efficiency perovskite solar cells (PSCs). However, scalable fabrication of SnO2 films with uniform coverage, desirable thickness and a low defect density in perovskite solar modules (PSMs) is still challenging. Here, we report preparation of high-quality large-area SnO2 films by chemical bath deposition (CBD) with the addition of KMnO4. The strong oxidizing nature of KMnO4 promotes the conversion from Sn(II) to Sn(VI), leading to reduced trap defects and a higher carrier mobility of SnO2. In addition, K ions diffuse into the perovskite film resulting in larger grain sizes, passivated grain boundaries, and reduced hysteresis of PSCs. Furthermore, Mn ion doping improves both the crystallinity and the phase stability of the perovskite film. Such a multifunctional interface engineering strategy enabled us to achieve a power conversion efficiency (PCE) of 21.70% with less hysteresis for lab-scale PSCs. Using this method, we also fabricated 5 × 5 and 10 × 10 cm2 PSMs, which showed PCEs of 15.62% and 11.80% (active area PCEs are 17.26% and 13.72%), respectively. For the encapsulated 5 × 5 cm2 PSM, we obtained a T80 operation lifetime (the lifespan during which the solar module PCE drops to 80% of its initial value) exceeding 1000 h in ambient condition.
Learning low-dimensional manifolds under the L0-norm constraint for unsupervised outlier detection
Authors: Ishii Yoshinao , Koide Satoshi , Hayakawa Keiichiro 
Published: July 2021

AbstractUnsupervised outlier detection without the need for clean data has attracted great attention because it is suitable for real-world problems as a result of its low data collection costs. Reconstruction-based methods are popular approaches for unsupervised outlier detection. These methods decompose a data matrix into low-dimensional manifolds and an error matrix. Then, samples with a large error are detected as outliers. To achieve high outlier detection accuracy, when data are corrupted by large noise, the detection method should have the following two properties: (1) it should be able to decompose the data under the L0-norm constraint on the error matrix and (2) it should be able to reflect the nonlinear features of the data in the manifolds. Despite significant efforts, no method with both of these properties exists. To address this issue, we propose a novel reconstruction-based method: “L0-norm constrained autoencoders (L0-AE).” L0-AE uses autoencoders to learn low-dimensional manifolds that capture the nonlinear features of the data and uses a novel optimization algorithm that can decompose the data under the L0-norm constraints on the error matrix. This novel L0-AE algorithm provably guarantees the convergence of the optimization if the autoencoder is trained appropriately. The experimental results show that L0-AE is more robust, accurate and stable than other unsupervised outlier detection methods not only for artificial datasets with corrupted samples but also artificial datasets with well-known outlier distributions and real datasets. Additionally, the results show that the accuracy of L0-AE is moderately stable to changes in the parameter of the constrained term, and for real datasets, L0-AE achieves higher accuracy than the baseline non-robustified method for most parameter values.
Atomic-Scale Friction Studies on Single-Crystal Gallium Arsenide Using Atomic Force Microscope and Molecular Dynamics Simulation
Authors: Fan Pengfei , Goel Saurav , Luo Xichun , Upadhyaya Hari M. 
Published: July 2021

AbstractThis paper provides a fresh perspective and new insights into nanoscale friction by investigating it through molecular dynamics (MD) simulation and atomic force microscope (AFM) nanoscratch experiments. This work considered gallium arsenide, an important III–V direct bandgap semiconductor material residing in the zincblende structure, as a reference sample material due to its growing usage in 5G communication devices. In the simulations, the scratch depth was tested as a variable in the fine range of 0.5–3 nm to understand the behavior of material removal and to gain insights into the nanoscale friction. Scratch force, normal force, and average cutting forces were extracted from the simulation to obtain two scalar quantities, namely, the scratch cutting energy (defined as the work performed to remove a unit volume of material) and the kinetic coefficient of friction (defined as the force ratio). A strong size effect was observed for scratch depths below 2 nm from the MD simulations and about 15 nm from the AFM experiments. A strong quantitative corroboration was obtained between the specific scratch energy determined by the MD simulations and the AFM experiments, and more qualitative corroboration was derived for the pile-up and the kinetic coefficient of friction. This conclusion suggests that the specific scratch energy is insensitive to the tool geometry and the scratch speed used in this investigation. However, the pile-up and kinetic coefficient of friction are dependent on the geometry of the tool tip.
Extreme Events, Entrepreneurial Start-Ups, and Innovation: Theoretical Conjectures
Authors: Gries Thomas , Naudé Wim 
Published: July 2021

AbstractIn light of the COVID-19 pandemic, we scrutinize what has been established in the literature on whether entrepreneurship can cause and resolve extreme events, the immediate and long-run impacts of extreme events on entrepreneurship, and whether extreme events can positively impact (some) entrepreneurship and innovation. Based on this, we utilize a partial equilibrium model to provide several conjectures on the impact of COVID-19 on entrepreneurship, and to derive policy recommendations for recovery. We illustrate that while entrepreneurship recovery will benefit from measures such as direct subsidies for start-ups, firms’ revenue losses, and loan liabilities, it will also benefit from aggregate demand-side support and income redistribution measures, as well as from measures that facilitate the innovation-response to the Keynesian supply-shock caused by the pandemic, such as access to online retail and well-functioning global transportation and logistics.
Health and safety control measures and MR quality control results in the MRI units of two public hospitals within the Mangaung metropolitan
Authors: Rathebe Phoka C. 
Published: July 2021

AbstractThis study aimed to identify risks and hazards in the magnetic resonance imaging (MRI) units, and assess the quality compliance of the scanners within two public hospitals in Mangaung. This is a follow-up study from a previously published study that measured static magnetic fields and radiofrequency magnetic fields in the MRI units included here. An observational checklist was used to identify risks and hazards which were later fed into a baseline risk assessment to classify and review existing control measures in the MRI units of hospitals A and B. The availability of MRI Health and Safety measures were benchmarked against the latest American College of Radiology (ACR) MRI safety requirements. The probability of risk occurrence and severity of hazards were assigned a score ranging from improbable (1) to very likely (5) and minimal (1) to irreversible effect (5). The weekly quality control test results obtained from both units were measured against the ACR quality control acceptable criteria. Similar risks were observed in both MRI units but the multiplication of probability and consequence in all risk categories resulted in a moderate risk-rating score of 12.3 for hospital A and 13.1 for hospital B. Lack of demarcation of four MRI safety zones, ferromagnetic detectors, 5-gauss line, and access control in both units scored above 15 and were classified as high risk. The defective air-cooling systems influenced the temperature of the scanner room, which affected the apparent diffusion coefficient (ADC) measurements performed from 1.5 T Siemens. On a 3.0 T Philips, a low contrast object detectability had 29 spokes for ACR T2, while the percent integral uniformity for image intensity uniformity was 78.2 %. High and moderate risks observed in both units could be reduced by the implementation of an effective health and safety programme. The ambient temperature within the scanner room should be maintained at 21 °C to attain well-performing ADC measurements and RF subsystems should be visually inspected and maintained regularly to obtain optimal image quality.
Collision Avoidance Using Deep Learning-Based Monocular Vision
Authors: Rill Róbert-Adrian , Faragó Kinga Bettina 
Published: July 2021

AbstractAutonomous driving technologies, including monocular vision-based approaches, are in the forefront of industrial and research communities, since they are expected to have a significant impact on economy and society. However, they have limitations in terms of crash avoidance because of the rarity of labeled data for collisions in everyday traffic, as well as due to the complexity of driving situations. In this work, we propose a simple method based solely on monocular vision to overcome the data scarcity problem and to promote forward collision avoidance systems. We exploit state-of-the-art deep learning-based optical flow and monocular depth estimation methods, as well as object detection to estimate the speed of the ego-vehicle and to identify the lead vehicle, respectively. The proposed method utilizes car stop situations as collision surrogates to obtain data for time to collision estimation. We evaluate this approach on our own driving videos, collected using a spherical camera and smart glasses. Our results indicate that similar accuracy can be achieved on both video sources: the external road view from the car’s, and the ego-centric view from the driver’s perspective. Additionally, we set forth the possibility of using spherical cameras as opposed to traditional cameras for vision-based automotive sensing.
Regulation of α‐cell glucagon secretion: The role of second messengers
Authors: Acreman Samuel , Zhang Quan 
Published: July 2021

AbstractGlucagon is a potent glucose‐elevating hormone that is secreted by pancreatic α‐cells. While well‐controlled glucagon secretion plays an important role in maintaining systemic glucose homeostasis and preventing hypoglycaemia, it is increasingly apparent that defects in the regulation of glucagon secretion contribute to impaired counter‐regulation and hyperglycaemia in diabetes. It has therefore been proposed that pharmacological interventions targeting glucagon secretion/signalling can have great potential in improving glycaemic control of patients with diabetes. However, despite decades of research, a consensus on the precise mechanisms of glucose regulation of glucagon secretion is yet to be reached. Second messengers are a group of small intracellular molecules that relay extracellular signals to the intracellular signalling cascade, modulating cellular functions. There is a growing body of evidence that second messengers, such as cAMP and Ca2+, play critical roles in α‐cell glucose‐sensing and glucagon secretion. In this review, we discuss the impact of second messengers on α‐cell electrical activity, intracellular Ca2+ dynamics and cell exocytosis. We highlight the possibility that the interaction between different second messengers may play a key role in the glucose‐regulation of glucagon secretion.