bluuebunny/crossref_metadata_2025_split huggingface dataset:
An alternative methodology addressing United Nations classification type for self‐reactive substances
Authors: Raines Elizabeth , Doup Benjamin 
Published: July 2022

AbstractThe UN “Recommendations on the Transport of Dangerous Goods” presents schemes for the classification of hazardous materials such as explosives, flammable liquids, or oxidizing substances, and gives descriptions of the test methods and procedures for the selection of appropriate packages and shipping types, as well as consignment procedures. Substances are classified according to their degree of danger, and the “Model Regulations” provide a hazard hierarchy. Class 4.1 and Class 5.2 materials are self‐reactive and solid desensitized explosives, and organic peroxides, respectively, and these hazard classes trump many other classification levels. The UN “Manual of Tests and Criteria” provides standard test methods for classifying self‐reactive and organic peroxide substances into seven groups (A–G) according to their hazard levels but also allows for other procedures to be used provided that adequate correlation has been obtained with the classification tests on a representative range of substances. There are eight test series (A–H) documented in the Manual of Tests and Criteria that could be needed in order to identify the hazard level for Class 4.1 and Class 5.2 materials, which can be an expensive and time‐consuming requirement. An alternative method aimed at streamlining the hazard classification process is proposed. This alternative method utilizes low phi‐factor adiabatic calorimetry data and the measured maximum rate of pressure rise to classify self‐reactive and organic peroxide substances for transport. Benchmarking experiments using this alternative method to classify t‐butyl perbenzoate, 50%–70% TBHP in decane, and 70% TBHP in water are promising, indicating that further evaluation of the proposed method is warranted.
Reliability analysis of complex electromechanical systems: State of the art, challenges, and prospects
Authors: Wang Rongxi , Xu Jinjin , Zhang Wenxin , Gao Jianmin , Li Yufan , Chen Fumin 
Published: July 2022

AbstractAs the core foundation of reliability engineering and one of the most crucial aspects of general quality, reliability has been attracting increasing attention from industry and academia. Numerous publications on reliability analysis (RA) have appeared in academic journals, conference proceedings, and technical reports. However, there has not been a systematic summary that covers RA data, models, methods, indicators, and software comprehensively. To fill this gap, this paper analyzed the challenges and the state of the art, as well as determined the future prospects for research on RA. This paper introduces the features of modern complex electromechanical systems (CES), then summarizes the current challenges to the RA of CES. Next, it reviews the latest developments, such as reliability theories, models, methods, and software, then summarizes and compares their advantages and limitations. Finally, it discusses future prospects from the perspectives of reliability data, modeling, decoupling, evaluation indicators, and timely prediction. It is expected that this paper would serve as an introduction to RA for researchers new to this field and as a summary of the current frontiers of RA for experienced researchers.
Universal MATLAB‐based square‐root solutions in the family of continuous‐discrete Gaussian filters for state estimation in nonlinear stochastic dynamic systems
Authors: Kulikov Gennady Yurievich , Kulikova Maria Vyacheslavovna 
Published: July 2022

AbstractThis article concerns with the issue of square‐rooting in continuous‐discrete Gaussian filters intended for state estimation in nonlinear stochastic dynamic systems of continuous‐discrete sort. These cover all methods devised within the quadrature, cubature, and unscented Kalman filtering approaches as well as those that can be constructed in the future. Based on the universal moment differential equations developed by Särkkä and Sarmavuori in 2013, we advance further that study and design two square‐root solutions grounded on MATLAB ODE solvers in the mentioned Gaussian filtering framework. The main problem addressed is a potential negativity of some weights utilized in calculations of the predicted and filtering means and covariances, which precludes from orthogonal square‐rooting schemes to be applied. In practice, such square‐root implementations are often requested because of their exceptional numerical robustness to round‐off and other disturbances. These also preserve the symmetry and positivity of the covariances computed, automatically. Here, we employ the recently‐devised ‐orthogonal square‐rooting technique for designing our universal MATLAB‐based square‐root solutions in the realm of quadrature, cubature, and unscented Kalman filters, which are easily adjusted to any particular method by using its weights and deterministically selected samples exploited in calculations of the sampled means and covariances. Such a ‐orthogonal square‐rooting approach is grounded on hyperbolic factorizations. It leads to two novel algorithms covering any continuous‐discrete Gaussian filter of the quadrature, cubature, or unscented Kalman‐like kind. Practical performances of our square‐root solutions are validated, assessed, and compared within two simulated ill‐conditioned scenarios in aeronautical and chemical engineering.
Distributed consensus control for networked Euler–Lagrange systems over directed graphs: A dynamic event‐triggered approach
Authors: Wei Minfeng , Xia Yuanqing , Zhang Yuan , Zhan Yufeng , Cui Bing 
Published: July 2022

AbstractThis paper considers the distributed dynamic event‐triggered consensus problem of multi‐agent systems with Euler–Lagrange dynamics over directed graphs in the presence of uncertain disturbances. To achieve consensus, a dynamic triggering law is designed such that consensus of reference model can be achieved. Different from the static triggering mechanism, an extra variable is involved in the proposed dynamic triggering law, which benefits the exclusion of the Zeno behavior. Then, an auxiliary variable is introduced to simplify agent dynamics, which benefits the controller design. Based on the auxiliary variable, a local controller is further proposed to guarantee the tracking ability of the auxiliary variable to the reference model. Owing to this treatment, consensus of agents can be reached in the presence of external disturbances. In addition, no continuous communication is needed in either controller updates or triggering detection. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed consensus protocol and its advantage in reducing the communication overhead compared with the relevant static triggering mechanism.
Triethanolamine modified graphene oxide for epoxy resin‐based coatings: Corrosion inhibition on metal substrates
Authors: Ban Chun‐guang , Zhang Kai , Huang Li , Yuan Ye 
Published: July 2022

Graphene oxide is an ideal nanofiller for epoxy resins because of its excellent mechanical properties, high thermal resistance, and abundant oxygen‐containing functional groups. However, the poor dispersion of graphene oxide in epoxy resins restricts its application in corrosive environments. In this study, epoxy coating was prepared by incorporating triethanolamine (TEA)‐modified graphene oxide (TEA‐GO‐EP). TEA acted as a modification agent for graphene oxide to improve its dispersion in epoxy and corrosion inhibitor for the underlying copper substrate. The long‐term potentiodynamic polarization and electrochemical impedance spectroscopy results demonstrated the improved anti‐corrosion performance of the TEA‐GO‐EP coatings in 3.5 wt.% NaCl aqueous solution, compared with the coatings without TEA. Moreover, the anti‐corrosion mechanism was discussed in detail. The findings reported in this paper have important implications for developing new types of eco‐friendly epoxy‐based coatings.
Peering into a crystal ball: Forecasting behavior and industry foresight
Authors: Kapoor Rahul , Wilde Daniel 
Published: July 2022

AbstractResearch SummaryWhat makes some managers and entrepreneurs better at forecasting the industry context than others? We argue that, regardless of experience or expertise, a learning‐based forecasting behavior in which individuals attend to and incorporate new relevant information from the environment into an updated belief that aligns with the Bayesian belief updating process is likely to generate superior industry foresight. However, the effectiveness of such a cognitively demanding process diminishes under high levels of uncertainty. We find support for these arguments using an experimental design of forecasting tournaments in the managerially relevant context of the global automotive industry from 2016 to 2019. The study provides a novel account of individual‐level forecasting behavior and its effectiveness in an evolving industry and suggests important implications for managers and entrepreneurs.Managerial SummaryHow a focal industry will evolve is a key forecasting problem faced by managers and entrepreneurs as they seek to identify opportunities and make strategic decisions. However, developing superior industry foresight in the face of significant change, and limited and often contradictory information, can be especially challenging. We study how individuals forecast the ongoing transformation of the global automotive industry with respect to electrification and autonomy, using a novel research design of forecasting tournaments. A forecasting process in which individuals update their beliefs by neither ignoring prior information nor overacting to new information helps to generate superior industry foresight. There was a significant penalty to forecasting accuracy when individuals did not update their beliefs at all, or when they updated, but overreacted to new information.
Hollow Aluminum Hydroxide Modified Silica Nanoadjuvants with Amplified Immunotherapy Effects through Immunogenic Cell Death Induction and Antigen Release
Authors: Tan Jia , Ding Binbin , Zheng Pan , Chen Hao , Ma Ping'an , Lin Jun 
Published: July 2022

AbstractIn spite of the widespread application of vaccine adjuvants in various preventive vaccines at present, the existing adjuvants are still hindered by weak cellular immunity responses in therapeutic cancer vaccines. Herein, a hollow silica nanoadjuvant containing aluminum hydroxide spikes on the surface (SiAl) is synthesized for the co‐loading of chemotherapeutic drug doxorubicin (Dox) and tumor fragment (TF) as tumor antigens (SiAl@Dox@TF). The obtained nanovaccines show significantly elevated anti‐tumor immunity responses thanks to silica and aluminum‐based composite nanoadjuvant‐mediated tumor antigen release and Dox‐induced immunogenic cell death (ICD). In addition, the highest frequencies of dendritic cells (DCs), CD4+ T cells, CD8+ T cells, and memory T cells as well as the best mice breast cancer (4T1) tumor growth inhibitory are also observed in SiAl@Dox@TF group, indicating favorable potential of SiAl nanoadjuvants for further applications. This work is believed to provide inspiration for the design of new‐style nanoadjuvants and adjuvant‐based cancer vaccines.
Engineering at Subatomic Scale: Achieving Selective Catalytic Pathways via Tuning of the Oxidation States in Functionalized Single‐Atom Quantum Catalysts
Authors: Zeb Akif , Sahar Shafaq , Lv Sheng‐Yao , Yousaf Ammar Bin , Kasak Peter , Lin Xiaoming , Tang Zhilie , Wu Yongbo , Li Guoliang , Xu An‐Wu 
Published: July 2022

AbstractRegulating the catalytic pathways of single‐atom sites in single atom catalysts (SACs) is an exciting debate at the moment, which has redirected the research towards understanding and modifying the single‐atom catalytic sites through various strategies including altering the coordination environment of single atom for desirable outcomes as well as increasing their number. One useful aspect concerning the tunability of the catalytic pathways of SACs, which has been overlooked, is the oxidation state dynamics of the single atoms. In this study, iron single‐atoms (FeSA) with variable oxidation states, dependent on the precursors, are harnessed inside a nitrogen‐rich functionalized carbon quantum dots (CQDs) matrix via a facile one‐step and low‐temperature synthesis process. Dynamic electronic properties are imparted to the FeSAs by the simpler carbon dots matrix of CQDs in order to achieve the desired catalytic pathways of reactive oxygen species (ROS) generation in different environments, which are explored experimentally and theoretically for an in‐depth understanding of the redox chemistry that drives the alternative catalytic pathways in FeSA@CQDs. These alternative and oxidation state‐dependent catalytic pathways are employed for specific as well as cascade‐like activities simulating natural enzymes as well as biomarkers for the detection of cancerous cells.
Lewis Acid Site Assisted Bifunctional Activity of Tin Doped Gallium Oxide and Its Application in Rechargeable Zn‐Air Batteries
Authors: Nair Aruna Narayanan , Sanad Mohamed F. , Jayan Rahul , Gutierrez Guillermo , Ge Yulu , Islam Md Mahbubul , Hernandez‐Viezcas Jose A. , Zade Vishal , Tripathi Shalini , Shutthanandan Vaithiyalingam , Ramana Chintalapalle V. , T. Sreenivasan Sreeprasad 
Published: July 2022

AbstractThe enhanced safety, superior energy, and power density of rechargeable metal‐air batteries make them ideal energy storage systems for application in energy grids and electric vehicles. However, the absence of a cost‐effective and stable bifunctional catalyst that can replace expensive platinum (Pt)‐based catalyst to promote oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) at the air cathode hinders their broader adaptation. Here, it is demonstrated that Tin (Sn) doped β‐gallium oxide (β‐Ga2O3) in the bulk form can efficiently catalyze ORR and OER and, hence, be applied as the cathode in Zn‐air batteries. The Sn‐doped β‐Ga2O3sample with 15% Sn (Snx=0.15‐Ga2O3) displayed exceptional catalytic activity for a bulk, non‐noble metal‐based catalyst. When used as a cathode, the excellent electrocatalytic bifunctional activity of Snx=0.15‐Ga2O3leads to a prototype Zn‐air battery with a high‐power density of 138 mW cm−2and improved cycling stability compared to devices with benchmark Pt‐based cathode. The combined experimental and theoretical exploration revealed that the Lewis acid sites in β‐Ga2O3aid in regulating the electron density distribution on the Sn‐doped sites, optimize the adsorption energies of reaction intermediates, and facilitate the formation of critical reaction intermediate (O*), leading to enhanced electrocatalytic activity.
Optically modulated dual‐mode memristor arrays based on core‐shell CsPbBr3@graphdiyne nanocrystals for fully memristive neuromorphic computing hardware
Authors: Wang Fu‐Dong , Yu Mei‐Xi , Chen Xu‐Dong , Li Jiaqiang , Zhang Zhi‐Cheng , Li Yuan , Zhang Guo‐Xin , Shi Ke , Shi Lei , Zhang Min , Lu Tong‐Bu , Zhang Jin 
Published: July 2022

AbstractArtificial synapses and neurons are crucial milestones for neuromorphic computing hardware, and memristors with resistive and threshold switching characteristics are regarded as the most promising candidates for the construction of hardware neural networks. However, most of the memristors can only operate in one mode, that is, resistive switching or threshold switching, and distinct memristors are required to construct fully memristive neuromorphic computing hardware, making it more complex for the fabrication and integration of the hardware. Herein, we propose a flexible dual‐mode memristor array based on core–shell CsPbBr3@graphdiyne nanocrystals, which features a 100% transition yield, small cycle‐to‐cycle and device‐to‐device variability, excellent flexibility, and environmental stability. Based on this dual‐mode memristor, homo‐material‐based fully memristive neuromorphic computing hardware—a power‐free artificial nociceptive signal processing system and a spiking neural network—are constructed for the first time. Our dual‐mode memristors greatly simplify the fabrication and integration of fully memristive neuromorphic systems.
Multi‐Phenotypic Exosome Secretion Profiling Microfluidic Platform for Exploring Single‐Cell Heterogeneity
Authors: Song Fangteng , Wang Chao , Wang Chunhua , Wang Jianbo , Wu Yu , Wang Yihe , Liu Hong , Zhang Yu , Han Lin 
Published: July 2022

AbstractCellular phenotypic and functional heterogeneities have advanced cancer evolution and treatment resistance. Although exosome‐bound proteins reflect cellular functions, single‐cell exosomes are rarely profiled owing to the lack of effective platforms. Herein, the authors developed an integrated microfluidic platform consisting of a single‐cell trapping chip and a spatially coded antibody barcode chip for the multiplexed outline of exosome secretion by single cells. Using this platform, five phenotypic exosomes of over 1 000 single cells are simultaneously profiled, in addition to inflammatory factor secretion from the same single cell. Also, a robust analysis workflow for single‐cell secretion profiling is proposed to explore the intercellular heterogeneity, which integrated unsupervised clustering and linear clustering. When applied to the tumor cell lines of epithelial‐origin and normal epithelial cell lines, the strategy identifies functionally heterogeneous subpopulations with unique secretion patterns. Notably, special functional cell subsets for unique phenotypic exosomes (HSP70+, EPCAM+) are found within ovarian tumor cells. The strategy proposed offers a new analysis approach for cellular differential exosome secretion at single‐cell resolution using inflammatory factors, ultimately reinforcing the understanding of cell‐to‐cell heterogeneity and tumor landscape, and providing a valuable universal platform for single‐cell biomarker exploration in biological and clinical research.
Continuous engineering for Industry 4.0 architectures and systems
Authors: Antonino Pablo Oliveira , Capilla Rafael , Kazman Rick , Kuhn Thomas , Schnicke Frank , Treichel Tagline , Bachorek Adam , Müller‐Zhang Zai , Salamanca Victor 
Published: July 2022

AbstractTraditionally, the quality of a software or system architecture has been evaluated in the early stages of the development process using architecture quality evaluation methods. Emergent approaches like Industry 4.0 require continuous monitoring of both run‐time and development‐time quality properties, in contrast to traditional systems where quality is evaluated at specific milestones using techniques such as project reviews. Considering the dynamics and minimum down‐time imposed by the industrial production domain, it must also be ensured that Industry 4.0 system evaluations are continuously performed with high confidence and with as much automation as possible, using simulations, for instance. In this regard, there is a need to develop new methods for continuously monitoring and evaluating the quality properties of software‐based systems for Industry 4.0, which must be supported by automated quality evaluation techniques. In this research we analyze traditional architecture evaluation methods and Industry 4.0 scenarios, and propose an approach based on Digital Twins and simulations to continuously evaluate runtime quality aspects of the architecture and systems of industrial production plants. The evaluation is based on the instantiation of our approach for a concrete demand of an automation plant in the automotive domain.
Alternative parameterization approaches for modelling risk assessment in the presence of imbalance: An example using parotid malignancy
Authors: Lo Kaming , Messinger Shari , Fundakowski Christopher , Sargi Zoukaa 
Published: July 2022

AbstractIn collaborative statistics, logistic regression models are commonly used with binary outcomes and reference cell coding for categorical predictors. However, despite the usefulness of reference cell coding schemes under many investigative objectives, it is not always appropriate to address research questions of interest. Investigators often consider modifying research questions to align with inference possible using reference cell coding. Alternative coding schemes can offer a more appropriate approach for the investigation. We explored application of deviation from means coding in determining how results from a diagnostic tool provide additional information on a patient's risk of disease with respect to the overall (naïve) risk at clinical presentation. We compared model parameterizations between using reference cell coding and deviation from means coding, by both unweighted and weighted approaches, for assessing risk of parotid malignancy, comparing patients with indeterminate FNAB results with the general (naïve) risk among presenting patients. Unweighted deviation from means coding estimates a 1.2‐fold increase in the odds of malignancy with an indeterminate FNAB result compared to the naïve odds of malignancy at clinical presentation (OR: 1.21 [95% CI: 1.63–2.32], p = 0.5699). The weighted approach takes into account the imbalance in the presenting population and estimates an increased risk (OR: 2.54 [95% CI: 1.52–4.26], p = 0.0004), which is more accurately representing the naïve risk at presentation and to answer the research question of interest. Using standard reference cell coding, an indeterminate result is associated with significantly higher odds than that of a negative result (OR: 5.20 [95% CI: 2.22–12.20], p = 0.0001), but this does not inform us as to the risk with respect to that inherent at clinical presentation and thus may not be useful for clinical decision making.
Synthesis and Properties of Stable 20π Porphyrinoids
Authors: Pushpanandan Poornenth , Ravikanth Mangalampalli 
Published: July 2022

AbstractThe 20π porphyrinoids are immediate higher homologues of 18π porphyrins and differ from porphyrins in aromaticity which in turn affects the structure, properties and chemical reactivities. Research over the years indicated that the 20π porphyrinoids can be stabilized as non‐aromatic/anti‐aromatic or Mobius aromatic macrocycles using different strategies such as core‐modification of porphyrins, non‐metal/metal complexation of porphyrins, peripheral modification of porphyrins and expanded porphyrinoids. The structural properties such as aromaticity of the macrocycle can be controlled by choosing the right synthetic strategy. This review will provide an overview of the development in the chemistry of 20π porphyrinoids giving emphasize on the synthesis, structure and electronic properties of these macrocycles which have huge potential for various applications.
Aneurysmal bone cyst in the scapula of a young cat
Authors: Manca Stefano , Mate de Haro Luis , Civello Alex , Martí Juan 
Published: July 2022

AbstractA 2‐year and 6‐month‐old male neutered domestic long hair cat was referred for assessment of right thoracic limb lameness of approximately 3 months’ duration. Palpation of the right shoulder revealed a firm mass of approximately 6 cm diameter centred on the mid‐body of the scapula. Computed tomography (CT) showed a lytic expansile mass on the caudo‐dorsal aspect of the right scapula. Differential diagnoses included reactive or reparative processes, sarcoma‐like lesions and aneurysmal bone cyst (ABC). Due to the potential for malignancy, a total scapulectomy was performed, and histopathology confirmed the final diagnosis of ABC. The patient recovered uneventfully from surgery, and 11 months following surgery showed a good return to function and an excellent level of comfort.