bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synergistic Integration and Pharmacomechanical Function of Enzyme‐Magnetite Nanoparticle Swarms for Low‐Dose Fast Thrombolysis
Authors: Tang Xiuzhen , Manamanchaiyaporn Laliphat , Zhou Qi , Huang Chenyang , Li Lihuang , Li Ziqiao , Wang Longchen , Wang Jienan , Ren Lei , Xu Tiantian , Yan Xiaohui , Zheng Yuanyi 
Published: July 2022

AbstractMagnetic micro‐/nanoparticles are extensively explored over the past decade as active diagnostic/therapeutic agents for minimally invasive medicine. However, sufficient function integration on these miniaturized bodies toward practical applications remains challenging. This work proposes a synergistic strategy via integrating particle functionalization and bioinspired swarming, demonstrated by recombinant tissue plasminogen activator modified magnetite nanoparticles (rtPA‐Fe3O4 NPs) for fast thrombolysis in vivo with low drug dosage. The synthesized rtPA‐Fe3O4 NPs exhibit superior magnetic performance, high biocompatibility, and thrombolytic enzyme activity. Benefiting from a customized magnetic operation system designed for animal experiments and preclinical development, these agglomeration‐free NPs can assemble into micro‐/milli‐scale swarms capable of robust maneuver and reconfigurable transformation for on‐demand tasks in complex biofluids. Specifically, the spinning mode of the swarm exerts focused fluid shear stresses while rubbing on the thrombus surface, constituting a mechanical force for clot breakdown. The synergy of the NPs’ inherent enzymatic effect and swarming‐triggered fluid forces enables amplified efficacy of thrombolysis in an in vivo occlusion model of rabbit carotid artery, using lower drug concentration than clinical dosage. Furthermore, swarming‐enhanced ultrasound signals aid in imaging‐guided treatment. Therefore, the pharmacomechanical NP swarms herein represent an injectable thrombolytic tool joining advantages of intravenous drug therapy and robotic intervention.
High‐Throughput Generation of 3D Graphene Metamaterials and Property Quantification Using Machine Learning
Authors: Yang Zhenze , Buehler Markus J. 
Published: July 2022

Abstract3D graphene assemblies are proposed as solutions to meet the goal toward efficient utilization of 2D graphene sheets, showing excellent performances in applications such as mechanical support, energy storage, and electrochemical catalysis. However, given the diversity and complexity of possible graphene 3D structures, there does not yet exist a systematic approach that can generate target 3D shapes and also, evaluate their performance. Here high‐throughput data generation is combined with artificial intelligence approaches to realize rapid structure formation and property quantification of 3D graphene foams with mathematically controlled topologies, driven by molecular dynamics simulations. More than 4000 different foam structures are created, which feature diverse topologies that contain potential pathways for small molecules and auxetic structures with negative Poisson's ratio. Empowered by machine learning (ML) algorithms including graph neural networks, not only global properties such as elastic moduli, but also local behaviors such as atomic stress can be predicted and optimized based on their atomic structure, bypassing expensive atomistic simulations. The key findings of the research reported in this paper include a high‐throughput virtual framework of generating diverse 3D graphene assemblies with mechanical performances quantification, and highly efficient methods of evaluating physical properties based on ML.
Engineering Anion‐Pillared Metal–Organic Frameworks for Record Acetylene/Methane Separation
Authors: Shao Kai , Wang Jia‐Xin , Pei Jiyan , Liu Di , Li Bin 
Published: July 2022

AbstractThe realization of ideal molecular sieves has a great potential to achieve the desired gas separations by fine‐tuning pore structures to generate suitable aperture sizes, which can be exclusive to larger molecules thus performing efficient separations. Despite numerous attempts, there are few developed porous materials that implement molecular sieving for C2H2/CH4 separation. Herein, we show how fine‐tuning of pore size in a series of selected SIFSIX materials achieves ideal molecular sieving for C2H2/CH4 separation at ambient conditions. With an optimized pore size of 3.4 Å and abundant binding sites in the channels, UTSA‐200 shows complete exclusion of larger CH4 molecules, while maintaining strong affinities toward C2H2. Therefore, this material exhibits both high uptake capacity at low pressure (up to 41 cm3 g−1 at 0.01 bar and 296 K) and record C2H2/CH4 selectivity (over 1×107). Dynamic breakthrough experiments validated the ideal sieving separation performance of UTSA‐200 for C2H2/CH4 mixtures, affording an exceptionally high C2H2 capacity of 73.5 L kg−1 with high purity of 99.5 % per cycle.
EMJM PROMISE—The New International Erasmus Mundus Joint Master in Sustainable Mineral and Metal Processing Engineering
Authors: Öfner Wolfgang , Sinche-Gonzalez Maria , Flachberger Helmut , Bedeković Gordan , Acuña Claudio , Guerra Paula 
Published: July 2022

AbstractThe challenge of attracting young people to the field of mineral processing as well as the ever-growing worldwide demand for minerals and metals together with lower-grade deposits and shortages of energy and water triggered the establishment of the new Erasmus Mundus Joint Master Program PROMISE. The consortium of four mining universities in Europe and Chile aims at master level education on engineering and sustainability issues in mineral processing. The first academic year of PROMISE will start in September 2022.
Formsteine – Eine technische Lösung, um kupferhaltige Rest- und Kreislaufstoffe ofengängig zu machen
Authors: Marousek Lukas , Böhm Andreas , Tripolt Thomas , Pesl Josef 
Published: July 2022

ZusammenfassungDer Schachtofen stellt einen wesentlichen Prozessschritt dar, um geringer Cu-haltige, sekundäre Einsatzstoffe für die nachfolgende Raffination zu erschließen. Der Gegenstromreaktor setzt allerdings ausreichende Stückigkeit und Temperaturstabilität bei geeigneter chemischer Zusammensetzung voraus. Für den Einsatz fein- und feinstkörniger Stoffe wie Schlämme, Granulate und Krätzen, deren Wiedereinsatz betriebsintern im Sinne der Kreislaufwirtschaft sowohl ökologisch wie auch ökonomisch höchst sinnvoll ist, werden neue Agglomerationstechniken zur Stückigmachung benötigt. Eine Möglichkeit bietet die aus der Betonsteinindustrie bekannte, vergleichsweise kostengünstige Steinpresse.Experimentelle Entwicklung nach der Methodik der statistischen Versuchsplanung führte systematisch von Kleinstversuchen im Labormaßstab mit speziell entwickelter Versuchsapparaten, über Pilotversuche, in denen Brikettgröße und Brikettform bereits mit dem industriellen Maßstab übereinstimmten, zur industriellen Anwendung. In der Prozessabfolge Dosieren, Mischen, Pressen, Aushärten wurden Rezepte für einzelne Einsatzstoffe auf Basis hydraulischer Bindemittel entwickelt, um die Festigkeit nach beschränkter Aushärtedauer zu optimieren.Die Erkenntnisse konnten unmittelbar in die industrielle Praxis umgesetzt werden.
„Smart Granulation“ – Sensorunterstützte Regelungskonzepte für Granulierprozesse mittels Pelletierteller
Authors: Reisinger Florian 
Published: July 2022

ZusammenfassungIm Zuge eines EU-Projektes arbeitet CEMTEC Cement and Mining Technology GmbH gemeinsam mit dem LCM Linz Center of Mechatronics GmbH an neuwertigen und innovativen Regelungsansätzen für Granulierprozesse mittels Pelletierteller. Es werden hierbei sowohl physikalisch basierte als auch datenbasierte Modelle in Form eines hybriden Systems kombiniert. Ziel des Projektes ist es, ein Regelsystem zu schaffen, das die jeweiligen Stärken der physikalischen und datenbasierten Modelle erkennt und situativ den optimalen Lösungsweg mit der maximal erzielbaren Anlagenenergieeffizienz wählt.
An automated framework for verifying or refuting trace properties of extended finite state machines
Authors: Taylor Ramsay G. , Foster Michael , North Siobhán 
Published: July 2022

AbstractModel checkers and interactive proof assistants are both used in the assurance of critical systems. Where theorem proving involves the use of axioms and inference rules to mathematically prove defined properties, model checkers can be used to provide concrete counterexamples to refute them. Thus, the two techniques can be thought of as complementary, and it is helpful to use both in tandem to take advantage of their respective strengths. However, this requires us to translate our system model and our desired properties between the two tools which is a time-consuming and error prone process if done manually. The key contribution of this work is a set of automated tools to translate between the Isabelle/HOL proof assistant and the Symbolic Analysis Laboratory (SAL) model checker. We focus on systems specified as extended finite state machines (EFSMs) and on properties specified in linear temporal logic (LTL). We present our representations in the two tools and demonstrate the applicability of our system with respect to an academic example and two realistic case studies. This is a significant contribution to broadening the applicability of these formal approaches, since it allows two powerful verification tools to be easily used in tandem without the risk of human error.
Multi-layer noise reshaping and perceptual optimization for effective adversarial attack of images
Authors: He Zhiquan , Lan Xujia , Yuan Jianhe , Cao Wenming 
Published: July 2022

AbstractAdversarial attack aims to fail the deep neural network by adding a small amount of perturbation to the input image, in which the attack success rate and resulting image quality are maximized under the lp norm perturbation constraint. However, the lp norm is not accurately correlated to human perception of image quality. Attack methods based on l0 norm constraint usually suffer from the high computational cost due to the iterative search for candidate pixels to modify. In this work, we explore how perceptual quality optimization can be incorporated into the adversarial attack design and propose a two-stage attack method to reshape the adversarial noise by an initial attack and optimize the visual quality of the attacked images without sacrificing the attack success rate. Specifically, we construct a visual attention network to generate a perceptual attention map to modulate the adversarial noise generated by a base attack method. The network is trained to maximize the visual quality in Structural Similarity Index Metric (SSIM) while achieving the same attack success rate. To improve the image perceptual quality further, we propose a fast search algorithm to perform an iterative block-wise pruning of the adversarial noise. We evaluate our method on the mini-ImageNet dataset against three different defense schemes. The results have demonstrated that our method can achieve better attack performance in image quality, attack success rate, and efficiency than the state-of-the-art attack methods.
Values and Multi-stakeholder Dialog for Business Transformation in Light of the UN Sustainable Development Goals
Authors: Sebhatu Samuel Petros , Enquist Bo 
Published: July 2022

AbstractThe objective of this article is to create an understanding of how the UN sustainable development goals (SDGs) can be used to steer stakeholder engagement for transformative change, meeting global challenges, and navigate a new business-societal practice driven by a values-based business model. The article is a conceptual study with case studies of the role that the SDGs play in multi-stakeholder dialog via the kind of sustainable business-societal practice that takes corporate social responsibility (CSR) to the next level, where it is embedded in a values-based business model, creating a new meaning to effect real business-societal transformation. Multi-stakeholder dialog implies interactive and communicative engagement with the full range of stakeholders in order to create value for all, employing a societal perspective and using the value network as a basis for effective decision-making. We explain our methodological approach by presenting multi-stakeholder dialog in practice, in the form of multiple case studies. These empirical settings consisted of two values-driven privately owned companies with a strong reporting mechanism and a clear transformation agenda based on the SDG challenges: IKEA and Löfbergs. The empirical study provides the basis for our proposed model. This article makes an original contribution to the study of the use of SDGs in management and service research. It investigates steering and navigating processes in specific contexts in order to determine what should be subject to legal enforcement and what comprises moral and/or ethical value, particularly at the societal level.
Using an unmanned aerial system to analyse environmental impacts of charcoal production on tropical savanna ecosystems in northwestern Kenya
Authors: Petersen Maike , Nüsser Marcus 
Published: July 2022

AbstractIn many regions of Sub-Saharan Africa, charcoal plays an important role as energy source but is widely perceived as a major driver of deforestation and forest degradation. This narrative, however, is mostly based on research within primary production regions. Though space-borne remote sensing applications can be useful in monitoring such large-scale production modes, environmental effects of household-level production are less easy to assess. Therefore, the present study employs an unmanned aerial system (UAS) to assess the impact of small-scale charcoal production on the vegetation density in the immediate vicinity of production sites. The UAS data was complemented by field measurements and very high-resolution WordView-2 satellite imagery. This approach revealed only small differences between charcoal production sites and reference plots which were usually evened out after 20–25-m distance to the plot centre using a concentric ring analysis. Results further show that a distinction between different land-use practices is difficult, even with the high spatial resolution provided by a UAS. Thus, more research and new approaches are needed to evaluate the role of small-scale charcoal production in deforestation and forest degradation processes against the background of other human activities. However, to exploit the full potential of UAS for monitoring environmental effects in charcoal producing areas, official regulations need to be clearer and more reliable.
Why We Need to Talk About Preferences: Economic Experiments and the Where-Question
Authors: Beck Lukas 
Published: July 2022

AbstractWhen economists perform experiments, they do so typically in one of two traditions: cognitive psychology experiments in the heuristics and biases tradition (H&B-experiments) and experimental economics in the tradition of Vernon Smith. What sets these two traditions apart? In this paper, I offer a novel conceptualization of their pervasive disagreements. Focusing on how each camp approaches preferences, one of the most fundamental concepts in economics, I argue that experimental economics can be reconstructed as holding that the constituents of preferences can be partially located in agents’ environments, while H&B-experiments implicitly assume that the constituents of preferences are entirely located within agents’ bodies. The paper (i) outlines how my reconstruction can account for the disagreement between the two paradigms, (ii) defends the plausibility of this reconstruction, and (iii) highlights its implications for the debate about the nature of preferences in economics.
Can we Bridge AI’s responsibility gap at Will?
Authors: Kiener Maximilian 
Published: July 2022

AbstractArtificial intelligence (AI) increasingly executes tasks that previously only humans could do, such as drive a car, fight in war, or perform a medical operation. However, as the very best AI systems tend to be the least controllable and the least transparent, some scholars argued that humans can no longer be morally responsible for some of the AI-caused outcomes, which would then result in a responsibility gap. In this paper, I assume, for the sake of argument, that at least some of the most sophisticated AI systems do indeed create responsibility gaps, and I ask whether we can bridge these gapsat will, viz. whether certain people couldtakeresponsibility for AI-caused harm simply by performing a certain speech act, just as people can give permission for something simply by performing the act of consent. So understood, taking responsibility would be a genuine normative power. I first discuss and reject the view of Champagne and Tonkens, who advocate a view of takingliability. According to this view, a military commander can and must, ahead of time, accept liability to blame and punishment for any harm caused by autonomous weapon systems under her command. I then defend my own proposal of takinganswerability, viz. the view that people can makes themselves morally answerable for the harm caused by AI systems, not only ahead of time but also when harm has already been caused.
“Employability in context”: graduate employability attributes expected by employers in regional Vietnam and implications for career guidance
Authors: Tran Ly Thi , Ngo Nga Thi Hang , Nguyen Hoa Thi Mai , Le Truc Thi Thanh , Ho Tien Thi Hanh 
Published: July 2022

AbstractThis article examines how graduate employability is viewed by employers in six economically disadvantaged mountainous provinces in Vietnam. The study reported in this article identified continuous self-learning, resilience, adaptability, devotion and empathy for the local people and local community to be among the main employability attributes expected of graduates in regional Vietnam. The findings of the study raise the importance of context situatedness in looking at employability and show how employability is characterised by the local structural conditions, demographic features and socio-cultural norms. The study provides significant implications for career guidance and graduate employability development, especially in relation to regional areas.
Wheat bran addition as potential alternative to control the plasticizer migration into PLA/PBSA blends
Authors: Aliotta Laura , Vannozzi Alessandro , Cinelli Patrizia , Fiori Stefano , Coltelli Maria-Beatrice , Lazzeri Andrea 
Published: July 2022

AbstractWheat bran (WB) was investigated as potential filler for controlling the plasticizer migration in poly(lactic acid) (PLA)/poly(butylene succinate adipate) (PBSA) binary blends (with 60 wt.% of PLA and 40 wt.% of PBSA). The migration process of three different biobased and biodegradable plasticizers [Triacetin (TA), acetyl tri-n-butyl citrate (ATBC) and oligomeric lactic acid (OLA)] was investigated adding them at a fixed amount of 10 wt.%. TA revealed the greater mass loss over the time as confirmed from the calculation of the diffusion coefficients. The addition of WB in different amount (from 10 to 30 wt.%) revealed its tendency to influence the diffusion process in a manner strictly dependent on its content. The great dimensions of the WB, however, weaken the material suggesting to adopt a preliminary dimensional reduction of the filler to mitigate the negative effect observed on the mechanical properties. From this study emerged the WB potential to be used as filler for controlling the plasticizer migration, thus suggesting a possible valorization of this waste byproduct in biobased and biodegradable materials.
Factors Affecting Australian Catholics’ Return to Mass After COVID-19 Church Closures
Authors: Martyr Philippa 
Published: July 2022

AbstractIn 2020, many places of worship closed due to COVID-19 restrictions, raising questions about rates of return to worship after COVID-19. This survey-based study of 806 Australian churchgoing Catholics explores relationships between a range of variables and the rate of return to Mass attendance after church closures. Pre-closure Mass attendance rate strongly and significantly predicted real-life worship during church closures and higher rates of return to Mass attendance after churches reopened. Real-life worship during COVID-19 also strongly predicted return to Mass attendance, and positively mediated the relationship between pre- and post-closure Mass attendance rates. Virtual worship engagement did not significantly predict return to Mass attendance, but positively mediated the relationship between pre- and post-closure Mass attendance rates, with a smaller effect size.
Crypto-marketing: how non-fungible tokens (NFTs) challenge traditional marketing
Authors: Hofstetter Reto , de Bellis Emanuel , Brandes Leif , Clegg Melanie , Lamberton Cait , Reibstein David , Rohlfsen Felicia , Schmitt Bernd , Zhang John Z. 
Published: July 2022

Abstract
In this article, we argue that non-fungible tokens (NFTs) challenge established marketing understanding of digital ownership, uniqueness, and value; authenticity, status, and sharing; and branding and distribution. We propose a set of preliminary research questions rooted in these areas, in hopes of offering entry points to future programmatic investigation of the broader field of “crypto-marketing.” This emerging subdiscipline offers opportunities to expand our understanding of consumer behavior, pricing, and product design and may be crucial in predicting the future of our discipline as NFTs further evolve.
Movement and cyclic Agree
Authors: Keine Stefan , Dash Bhamati 
Published: July 2022

AbstractRecent work has argued for derivational expansion of the search space of ɸ-probes as a result of the cyclic interaction of Merge and Agree (cyclic Agree). Empirical evidence for such effects has come from the interaction of Agree with external Merge, but these accounts make the additional predictions that such interactions should also arise from the interaction of Agree with movement. In this paper, we argue based on evidence from Hindi-Urdu that movement may feed cyclic Agree in the same way as external Merge, bearing out this key prediction. The central empirical generalizations that we argue for are that (i) A-scrambling of an object over a subject may feed agreement in certain configurations, (ii) there is nonetheless a preference for agreement with the structurally lower subject, and (iii)$\overline {\text{A}}$A‾-scrambling of the object never feeds agreement. We develop a cyclic-Agree analysis that provides a principled explanation of these generalizations. Crucial to this explanation are that (i) search space is dynamic and interacts with movement, (ii) there is a preference for agreement with elements c-commanded by the head that hosts the probe (first-cycle Agree), and (iii) ɸ-probes project as part of the label, but not past the immediate projection line of the head.