bluuebunny/crossref_metadata_2025_split huggingface dataset:
A comparative study of unpasteurized and pasteurized frozen whole hen eggs using size-exclusion chromatography and small-angle X-ray scattering
Authors: Oka Yoshiki , Yukawa Hiroko , Kudo Hisashi , Ooka Koji , Wada Manami , Suetaka Shunji , Chang Mari , Kawai Hidenobu , Tanaka Ryouji , Ichikawa Masahiro , Suzuki Takahisa , Hayashi Yuuki , Handa Akihiro , Arai Munehito 
Published: June 2022

AbstractHen eggs are rich in proteins and are an important source of protein for humans. Pasteurized frozen whole hen eggs are widely used in cooking and confectionery and can be stored for long periods. However, processed eggs differ from raw eggs in properties such as viscosity, foaming ability, and thermal aggregation. To develop pasteurized frozen whole egg products with properties similar to those of unpasteurized whole eggs, it is necessary to establish a method that can differentiate between the two egg types with respect to the structures of their proteins. In this study, size-exclusion chromatography (SEC) and SEC coupled with small-angle X-ray scattering (SEC-SAXS) were successfully used to differentiate between the proteins in unpasteurized and pasteurized frozen whole eggs. We found that proteins in the plasma fraction of egg yolk, especially apovitellenins I and II, formed large aggregates in the pasteurized eggs, indicating that their structures are sensitive to temperature changes during pasteurization, freezing, and thawing. The results suggest that SEC and SEC-SAXS can be used to differentiate between unpasteurized and pasteurized frozen whole eggs. Additionally, they may be useful in determining molecular sizes and shapes of multiple components in various complex biological systems such as whole eggs.
Combined use of conventional and clumped carbonate stable isotopes to identify hydrothermal isotopic alteration in cave walls
Authors: Temovski Marjan , Rinyu László , Futó István , Molnár Kata , Túri Marianna , Demény Attila , Otoničar Bojan , Dublyansky Yuri , Audra Philippe , Polyak Victor , Asmerom Yemane , Palcsu László 
Published: June 2022

AbstractAlteration of conventional carbonate stable isotopes (δ18O, δ13C) in cave walls has been shown to be a useful tool to identify cave formation driven by deep-seated processes, i.e., hypogene karstification. If combined with a prior information on the paleowater stable isotope composition, further insights can be obtained on the temperature and the source of the paleowater. Clumped isotope composition (Δ47) of carbonates is an independent measurement of temperature, and if combined with the conventional stable isotopes, can provide information on the paleowater stable isotope composition. On the example of Provalata Cave (N. Macedonia), we apply for the first time, both conventional and clumped stable isotope analysis, and identify two different isotope alteration trends, reflecting two distinct hydrothermal events: an older, hotter one, where isotope alteration was likely related to isotope diffusion, lowering the δ18O values of the carbonate; and a younger one, related to the cave formation by low-temperature CO2-rich thermal waters, with dissolution-reprecipitation as the alteration mechanism, causing decrease in δ18O values, and unexpected increase in δ13C values. The findings are further corroborated by additional insight from optical petrography and cathodoluminescence microscopy, as well as fluid inclusion analysis of secondary calcite crystals related to the cave forming phase.
Effect of simultaneous testing of two mice in the tail suspension test and forced swim test
Authors: Ueno Hiroshi , Takahashi Yu , Murakami Shinji , Wani Kenta , Matsumoto Yosuke , Okamoto Motoi , Ishihara Takeshi 
Published: June 2022

AbstractIn mouse studies, the results of behavioural experiments are greatly affected by differences in the experimental environment and handling methods. The Porsolt forced swim test and tail suspension test are widely used to evaluate predictive models of depression-like behaviour in mice. It has not been clarified how the results of these tests are affected by testing single or multiple mice simultaneously. Therefore, this study evaluated the differences between testing two mice simultaneously or separately. To investigate the effect of testing multiple mice simultaneously, the Porsolt forced swim test and tail suspension test were performed in three patterns: (1) testing with an opaque partition between two mice, (2) testing without a partition between two mice, and (3) testing a single mouse. In the Porsolt forced swim test, the mice tested simultaneously without a partition demonstrated increased immobility time as compared to mice tested alone. No difference in immobility time was observed between the three groups in the tail suspension test. Our results showed that the environment of behavioural experiments investigating depression-like behaviour in mice can cause a difference in depression-like behaviour. The results of this experiment indicated that it is necessary to describe the method used for behavioural testing in detail.
Daily and seasonal heat usage patterns analysis in heat networks
Authors: Dang L. Minh , Lee Sujin , Li Yanfen , Oh Chanmi , Nguyen Tan N. , Song Hyoung-Kyu , Moon Hyeonjoon 
Published: June 2022

AbstractHeat usage patterns, which are greatly affected by the users' behaviors, network performances, and control logic, are a crucial indicator of the effective and efficient management of district heating networks. The variations in the heat load can be daily or seasonal. The daily variations are primarily influenced by the customers' social behaviors, whereas the seasonal variations are mainly caused by the large temperature differences between the seasons over the year. Irregular heat load patterns can significantly raise costs due to pricey peak fuels and increased peak heat load capacities. The in-depth analyses of heat load profiles are regrettably quite rare and small-scale up until now. Therefore, this study offers a comprehensive investigation of a district heating network operation in order to exploit the major features of the heat usage patterns and discover the big factors that affect the heat load patterns. In addition, this study also provides detailed explanations of the features that can be considered the main drivers of the users' heat load demand. Finally, two primary daily heat usage patterns are extracted, which are exploited to efficiently train the prediction model.
Dysregulation of microRNAs and tRNA-derived ncRNAs in mesothelial and mesothelioma cell lines after asbestiform fiber exposure
Authors: Filetti Veronica , La Ferlita Alessandro , Di Maria Antonio , Cardile Venera , Graziano Adriana C. E. , Rapisarda Venerando , Ledda Caterina , Pulvirenti Alfredo , Loreto Carla 
Published: June 2022

AbstractExperimental evidence demonstrated that fluoro-edenite (FE) can develop chronic respiratory diseases and elicit carcinogenic effects. Environmental exposure to FE fibers is correlated with malignant pleural mesothelioma (MPM). An early diagnosis of MPM, and a comprehensive health monitoring of the patients exposed to FE fibers are two clinical issues that may be solved by the identification of specific biomarkers. We reported the microRNA (miRNA) and transfer RNA-derived non coding RNA (tRNA-derived ncRNA) transcriptome in human normal mesothelial and malignant mesothelioma cell lines exposed or not exposed to several concentration FE fibers. Furthermore, an interactive mesothelioma-based network was derived by using NetME tool. In untreated condition, the expression of miRNAs and tRNA-derived ncRNAs in tumor cells was significantly different with respect to non-tumor samples. Moreover, interesting and significant changes were found after the exposure of both cells lines to FE fibers. The network-based pathway analysis showed several signaling and metabolic pathways potentially involved in the pathogenesis of MPM. From papers analyzed by NetME, it is clear that many miRNAs can positively or negatively influence various pathways involved in MPM. For the first time, the analysis of tRNA-derived ncRNAs molecules in the context of mesothelioma has been made by using in vitro systems. Further studies will be designed to test and validate their diagnostic potential in high-risk individuals' liquid biopsies.
One-component quantum mechanics and dynamical leakage-free paths
Authors: Jing Jun , Wu Lian-Ao 
Published: June 2022

AbstractWe derive an exact one-component equation of motion for the probability amplitude of a target time-dependent state, and use the equation to reformulate quantum dynamics and control for both closed and open systems. Using the one-component equation, we show that an unexpected time-dependent leakage-free path can be induced and we capture a necessary quantity in determining the effect of decoherence suppression. Our control protocol based on the nonperturbative leakage elimination operator provides a unified perspective connecting some subtle, popular, and important concepts of quantum control, such as dynamical decoupling, quantum Zeno effect, and adiabatic passage. The resultant one-component equation will promise significant advantages in both quantum dynamics and control.
Resistivity and thermal conductivity of an organic insulator β′–EtMe3Sb[Pd(dmit)2]2
Authors: Yamashita Minoru , Sato Yuki , Kasahara Yuichi , Kasahara Shigeru , Shibauchi Takasada , Matsuda Yuji 
Published: June 2022

AbstractA finite residual linear term in the thermal conductivity at zero temperature in insulating magnets indicates the presence of gapless excitations of itinerant quasiparticles, which has been observed in some candidate materials of quantum spin liquids (QSLs). In the organic triangular insulator β′–EtMe3Sb[Pd(dmit)2]2, a QSL candidate material, the low-temperature thermal conductivity depends on the cooling process and the finite residual term is observed only in samples with large thermal conductivity. Moreover, the cooling rate dependence is largely sample dependent. Here we find that, while the low-temperature thermal conductivity significantly depends on the cooling rate, the high-temperature resistivity is almost perfectly independent of the cooling rate. These results indicate that in the samples with the finite residual term, the mean free path of the quasiparticles that carry the heat at low temperatures is governed by disorders, whose characteristic length scale of the distribution is much longer than the electron mean free path that determines the high-temperature resistivity. This explains why recent X-ray diffraction and nuclear magnetic resonance measurements show no cooling rate dependence. Naturally, these measurements are unsuitable for detecting disorders of the length scale relevant for the thermal conductivity, just as they cannot determine the residual resistivity of metals. Present results indicate that very careful experiments are needed when discussing itinerant spin excitations in β′–EtMe3Sb[Pd(dmit)2]2.
A computational model of organism development and carcinogenesis resulting from cells’ bioelectric properties and communication
Authors: Carvalho Joao 
Published: June 2022

AbstractA sound theory of biological organization is clearly missing for a better interpretation of observational results and faster progress in understanding life complexity. The availability of such a theory represents a fundamental progress in explaining both normal and pathological organism development. The present work introduces a computational implementation of some principles of a theory of organism development, namely that the default state of cells is proliferation and motility, and includes the principle of variation and organization by closure of constraints. In the present model, the bioelectric context of cells and tissue is the field responsible for organization, as it regulates cell proliferation and the level of communication driving the system’s evolution. Starting from a depolarized (proliferative) cell, the organism grows to a certain size, limited by the increasingly polarized state after successive proliferation events. The system reaches homeostasis, with a depolarized core (proliferative cells) surrounded by a rim of polarized cells (non-proliferative in this condition). This state is resilient to cell death (random or due to injure) and to limited depolarization (potentially carcinogenic) events. Carcinogenesis is introduced through a localized event (a spot of depolarized cells) or by random depolarization of cells in the tissue, which returns cells to their initial proliferative state. The normalization of the bioelectric condition can reverse this out-of-equilibrium state to a new homeostatic one. This simplified model of embryogenesis, tissue organization and carcinogenesis, based on non-excitable cells’ bioelectric properties, can be made more realistic with the introduction of other components, like biochemical fields and mechanical interactions, which are fundamental for a more faithful representation of reality. However, even a simple model can give insight for new approaches in complex systems and suggest new experimental tests, focused in its predictions and interpreted under a new paradigm.
Light absorption enhancement in thin film GaAs solar cells using dielectric nanoparticles
Authors: Chaudhry Fateh A. , Escandell Lorena , López-Fraguas Eduardo , Vergaz Ricardo , Sánchez-Pena José Manuel , García-Cámara Braulio 
Published: June 2022

AbstractCost-effective and lightweight solar cells are currently demanded in strategic fields such as space applications or integrated-wearable devices. A reduction of the active layer thickness, producing thin-film devices, has been a traditional solution to accomplish both requirements. However, this solution also reduces the efficiency of the device. For this reason, alternative strategies are being proposed. In this work, light trapping effects of an array of semiconductor nanoparticles located on the top surface of a thin-film GaAs solar cell are investigated to improve the optical absorption and current density in active layer, under the standard AM-1.5 solar spectrum. The numerical results are compared with other previous proposals such as an aluminum nanoparticle array, as well as conventional solar cells with and without a standard anti-reflective coating (ARC). The inclusion of semiconductor nanoparticles (NPs) shows an improved response of the solar cells at different angles of incidence in comparison to solar cell with an ARC. Furthermore, the efficiency increases a 10% respect to the aluminum nanoparticles (NPs) architecture, and a 21% and a 30% respect to solar cells with and without ARC, respectively.
Impact of preoperative laboratory frailty index on mortality and clinical outcomes in older surgical patients with cancer
Authors: Kim Yoonjoo , Song Kijun , Kang Chang Moo , Lee Hyangkyu 
Published: June 2022

AbstractFrailty in older patients is associated with poor postoperative outcomes. The use of uncomplicated frailty measurement tools is preferred in busy clinical settings. Therefore, we validated the frailty index using routine laboratory data and the surgical outcomes of older patients with cancer who underwent cancer resection. We retrospectively analyzed 9015 patients aged 65 years and older who underwent cancer resection at a single tertiary hospital. Based on electronic-medical-record data regarding preoperative blood test results and vital signs, Laboratory Frailty Index (FI-Lab) scores were generated to measure preoperative frailty. The associations of FI-Lab with postoperative length of stay (LOS), readmission within 30 days, intensive care unit (ICU) admission within 30 days, and mortality were evaluated. The mean FI-Lab score of the 9015 patients was 0.20 ± 0.10. Increased FI-Lab scores (0.25–0.4; > 0.4) were associated with longer LOS, increased readmission within 30 days of surgery, ICU admission, and increased mortality, compared with FI-Lab scores < 0.25. The FI-Lab score, as a frailty indicator, was able to predict the risk of poor postoperative outcomes. Therefore, the FI-Lab is a potentially useful tool for assessing preoperative frailty in older patients with cancer in acute clinical setting.
Feature selection for global tropospheric ozone prediction based on the BO-XGBoost-RFE algorithm
Authors: Zhang Biao , Zhang Ying , Jiang Xuchu 
Published: June 2022

AbstractOzone is one of the most important air pollutants, with significant impacts on human health, regional air quality and ecosystems. In this study, we use geographic information and environmental information of the monitoring site of 5577 regions in the world from 2010 to 2014 as feature input to predict the long-term average ozone concentration of the site. A Bayesian optimization-based XGBoost-RFE feature selection model BO-XGBoost-RFE is proposed, and a variety of machine learning algorithms are used to predict ozone concentration based on the optimal feature subset. Since the selection of the underlying model hyperparameters is involved in the recursive feature selection process, different hyperparameter combinations will lead to differences in the feature subsets selected by the model, so that the feature subsets obtained by the model may not be optimal solutions. We combine the Bayesian optimization algorithm to adjust the parameters of recursive feature elimination based on XGBoost to obtain the optimal parameter combination and the optimal feature subset under the parameter combination. Experiments on long-term ozone concentration prediction on a global scale show that the prediction accuracy of the model after Bayesian optimized XGBoost-RFE feature selection is higher than that based on all features and on feature selection with Pearson correlation. Among the four prediction models, random forest obtained the highest prediction accuracy. The XGBoost prediction model achieved the greatest improvement in accuracy.
Urban climate changes during the COVID-19 pandemic: integration of urban-building-energy model with social big data
Authors: Takane Yuya , Nakajima Ko , Kikegawa Yukihiro 
Published: June 2022

AbstractThe changes in human behaviour associated with the spread of COVID-19 infections have changed the urban environment. However, little is known about the extent to which they have changed the urban climate, especially in air temperature (T), anthropogenic heat emission (QF) and electricity consumption (EC). We quantitatively evaluated these effects using a unique method that integrates real-time human population data (social big data) with an urban climate model. The results showed that in an office district in the city centre of Tokyo, the biggest metropolis in the world, under a significantly reduced population,EC(CO2emissions) would be 30% andQFwould be 33% of pre-COVID levels (without the stay-at-home advisories). This resulted in aTdecrease of about 0.2 °C, representing about 20% of the past greenhouse gas-induced warming (about 1.0 °C) in Tokyo. This method can be benchmarked and then applied to worldwide. The results suggest that changes in human behaviour can represent an adaptation and decarbonising strategies to climate change in cities.
Atomically dispersed Pt and Fe sites and Pt–Fe nanoparticles for durable proton exchange membrane fuel cells
Authors: Xiao Fei , Wang Qi , Xu Gui-Liang , Qin Xueping , Hwang Inhui , Sun Cheng-Jun , Liu Min , Hua Wei , Wu Hsi-wen , Zhu Shangqian , Li Jin-Cheng , Wang Jian-Gan , Zhu Yuanmin , Wu Duojie , Wei Zidong , Gu Meng , Amine Khalil , Shao Minhua 
Published: June 2022

AbstractProton exchange membrane fuel cells convert hydrogen and oxygen into electricity without emissions. The high cost and low durability of Pt-based electrocatalysts for the oxygen reduction reaction hinder their wide application, and the development of non-precious metal electrocatalysts is limited by their low performance. Here we design a hybrid electrocatalyst that consists of atomically dispersed Pt and Fe single atoms and Pt–Fe alloy nanoparticles. Its Pt mass activity is 3.7 times higher than that of commercial Pt/C in a fuel cell. More importantly, the fuel cell with a low Pt loading in the cathode (0.015 mgPt cm−2) shows an excellent durability, with a 97% activity retention after 100,000 cycles and no noticeable current drop at 0.6 V for over 200 hours. These results highlight the importance of the synergistic effects among active sites in hybrid electrocatalysts and provide an alternative way to design more active and durable low-Pt electrocatalysts for electrochemical devices.
Computational methods to simulate molten salt thermophysical properties
Authors: Porter Talmage , Vaka Michael M. , Steenblik Parker , Della Corte Dennis 
Published: June 2022

AbstractMolten salts are important thermal conductors used in molten salt reactors and solar applications. To use molten salts safely, accurate knowledge of their thermophysical properties is necessary. However, it is experimentally challenging to measure these properties and a comprehensive evaluation of the full chemical space is unfeasible. Computational methods provide an alternative route to access these properties. Here, we summarize the developments in methods over the last 70 years and cluster them into three relevant eras. We review the main advances and limitations of each era and conclude with an optimistic perspective for the next decade, which will likely be dominated by emerging machine learning techniques. This article is aimed to help researchers in peripheral scientific domains understand the current challenges of molten salt simulation and identify opportunities to contribute.
Statistical channel modelling of full‐angle 3.5 GHz OAM in indoor corridor scenario
Authors: Wang Yang , Shi Panpan , Liao Xi , Tennant A. 
Published: June 2022

AbstractA 3.5 GHz OAM antenna with ±1 mode was designed and fabricated, and the channel measurement in frequency domain was used to measure the channel in full angle domain under indoor multipath scenarios. Then, the modified probability density function of Gaussian distribution, Laplacian distribution, and Von Mises distribution are used to establish the OAM full‐angle statistical channel model. The fitting curve results well represent the statistical characteristics of OAM in indoor multipath scenario.
Full‐state discrete‐time model‐based stability analysis and parameter design of dual active bridge converter in energy storage system
Authors: Xiao Zhongxiu , Lei Wanjun , Xiang Zhangwei , Yin Yilin , Wang Wenhua 
Published: June 2022

AbstractThe dual active bridge (DAB) converter plays a crucial role in energy storage system application of DC microgrid. In such a cascade system, maintaining its stability is imperative for reliable operation of the DAB converter under constant current, constant power, and constant voltage charging mode. Firstly, the accurate discrete‐time models considering parasitic resistances are applied for three charging modes to reveal the system dynamic characteristics. The discrete‐time small‐signal models for different operation modes are developed further which gives guidance in the controller's parameters design. Secondly, the comprehensive and systematic analysis of all the possible unstable phenomena for three charging modes are conducted according to the discrete‐time model. Finally, the underlying mechanisms are revealed by analyzing the relationships among the state variables, the Floquet multipliers, and system parameters. It is demonstrated that the inductor and output capacitor of the DAB converter, the DC bus voltage, the equivalent series resistance of the battery, and the proportional constant can influence the system stability under all charging modes greatly. Hence, the stability‐oriented parameter design process is given which can provide the guidance in practical. The theoretical analysis under these three types operating modes is verified by simulations and experimental results.