bluuebunny/crossref_metadata_2025 huggingface dataset:
Regiochemical effects for the mechanochemical activation of 9‐π‐extended anthracene‐maleimide Diels–Alder adducts
Authors: Baumann Christoph , Willis‐Fox Niamh , Campagna Davide , Rognin Etienne , Marten Paul , Daly Ronan , Göstl Robert
Published: July 2022

The attachment point of the polymer chain to a force‐responsive molecular unit (mechanophore) is a decisive parameter determining bond scission rate and ultimately the mechanochemical reaction outcome. However, such regiochemical polymer substituent effects have not yet been investigated for 9‐π‐extended anthracene‐maleimide Diels‐Alder adducts. Here we combine three methods, namely ultrasonication, CoGEF computation, and flow activation, to understand the influence of the pulling point location on the mechanochemical reactivity of this mechanophore class. We find minor mechanochemical reactivity differences between the investigated constitutional mechanophore isomers. Concomitantly, our results highlight the capabilities and limitations of the employed experimental techniques for such delicate variances and raise the question whether these are relevant for mechanochemical applications in a material context.
Lupin causes maize to increase organic acid exudation and phosphorus concentration in intercropping
Authors: Schwerdtner Ulrike , Lacher Ulrike , Spohn Marie
Published: July 2022

Purpose

There is a need to develop agricultural practices that mobilize sparingly soluble soil phosphorus (P) due to increasing scarcity of P fertilizer. Interactions of different plant species in the rhizosphere might increase P mobilization, but the underlying mechanisms are still not fully understood.

Methods

We conducted a pilot study with four plant species (maize, soy, lupin, mustard) grown alone and in combination with maize (intercropping) to investigate how species interact to mobilize P from iron phosphate (FePO4). Root exudates of individual plants were collected and analyzed for low molecular weight organic acid anions (LMWOA) and pH.

Results

Maize increased its exudation of LMWOA and its biomass P concentration in intercropping, especially when grown together with lupin. This is the first study to show unequivocally that a high LMWOA concentration in the rhizosphere in intercropping is not only caused by high LMWOA release of the companion but also by an increased LMWOA exudation of the main crop. The high release of LMWOA was associated with a higher maize P concentration, indicating that enhanced LMWOA release in intercropping is beneficial for P acquisition of maize. Moreover, lupin and mustard mobilized more P from FePO4than maize and soy likely through high LMWOA exudation (lupin) and rhizosphere alkalinization (mustard).

Conclusion

Taken together, we reveal that intercropping with lupin increases the release of LMWOA by maize and concurrently the maize P concentration, suggesting that intercropping is useful for the mobilization of P from FePO4because it affects the exudation of maize.
Revealing and Controlling Energy Barriers and Valleys at Grain Boundaries in Ultrathin Organic Films
Authors: Walter Lisa S. , Axt Amelie , Borchert James W. , Kammerbauer Theresa , Winterer Felix , Lenz Jakob , Weber Stefan A. L. , Weitz R. Thomas
Published: July 2022

In organic electronics, local crystalline order is of critical importance for the charge transport. Grain boundaries between molecularly ordered domains are generally known to hamper or completely suppress charge transfer and detailed knowledge of the local electronic nature is critical for future minimization of such malicious defects. However, grain boundaries are typically hidden within the bulk film and consequently escape observation or investigation. Here, a minimal model system in form of monolayer‐thin films with sub‐nm roughness of a prototypical n‐type organic semiconductor is presented. Since these films consist of large crystalline areas, the detailed energy landscape at single grain boundaries can be studied using Kelvin probe force microscopy. By controlling the charge‐carrier density in the films electrostatically, the impact of the grain boundaries on charge transport in organic devices is modeled. First, two distinct types of grain boundaries are identified, namely energetic barriers and valleys, which can coexist within the same thin film. Their absolute height is found to be especially pronounced at charge‐carrier densities below 1012 cm–2—the regime at which organic solar cells and light emitting diodes typically operate. Finally, processing conditions by which the type or energetic height of grain boundaries can be controlled are identified.
Aqueous Dispersion of Carbon Nanomaterials with Cellulose Nanocrystals: An Investigation of Molecular Interactions
Authors: Aramfard Mohammad , Kaynan Ozge , Hosseini Ehsan , Zakertabrizi Mohammad , Pérez Lisa M. , Asadi Amir
Published: July 2022

Dispersing carbon nanomaterials in solvents is effective in transferring their significant mechanical and functional properties to polymers and nanocomposites. However, poor dispersion of carbon nanomaterials impedes exploiting their full potential in nanocomposites. Cellulose nanocrystals (CNCs) are promising for dispersing and stabilizing pristine carbon nanotubes (pCNTs) and graphene nanoplatelets (pGnP) in protic media without functionalization. Here, the underlying mechanisms at the molecular level are investigated between CNC and pCNT/pGnP that stabilize their dispersion in polar solvents. Based on the spectroscopy and microscopy characterization of CNCpCNT/pGnP and density functional theory (DFT) calculations, an additional intermolecular mechanism is proposed between CNC and pCNT/pGnP that forms carbonoxygen covalent bonds between hydroxyl end groups of CNCs and the defected sites of pCNTs/pGnPs preventing re‐agglomeration in polar solvents. This work's findings indicate that the CNC‐assisted process enables new capabilities in harnessing nanostructures at the molecular level and tailoring the performance of nanocomposites at higher length scales.
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

Magnetic 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

3D 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.
A Theoretical Perspective on the Thermodynamic Stability of Polymer Blends for Solar Cells: From Experiments to Predictive Modeling
Authors: Caddeo Claudia , Ackermann Jörg , Mattoni Alessandro
Published: July 2022

An overview of the theoretical/computational methods that allow the study of the thermodynamic stability of the polymer blends for photovoltaics is provided. After discussing the fundamental concepts of thermodynamic blend stability and solubility, including mixing enthalpy and the Flory–Huggins theory, some experimental approaches to determine the interaction parameter and the stability in organic photovoltaic (OPV) are briefly discussed, and the advances in the modeling of polymer blends based on the use of atomistic simulations and multiscale modeling are reviewed. An outlook on the modeling strategies that can have a strong impact on the design of stable blends and to the commercial OPV technologies is given. In particular, the main directions along which major developments are expected are envisaged: multiscale models with improved accuracy or machine learning methods applied to large ab initio datasets, as well as a judicious combination of the two strategies.
Metal Sulfides for Photocatalytic Hydrogen Production: Current Development and Future Challenges
Authors: Zhang Gongxin , Guan Zhongjie , Yang Jianjun , Li Qiuye , Zhou Yong , Zou Zhigang
Published: July 2022

Photocatalytic hydrogen production using semiconductor photocatalysts provides a promising strategy for solving the energy crisis. Metal sulfide photocatalysts have received extensive attention due to its visible‐light response, adjustable band structures, and relatively mild preparation conditions. In this review, the emerging strategies to improve photocatalytic performance and stability of metal sulfides are summarized, including engineering of heterojunction, defect engineering, loading single‐atom cocatalyst, photothermal effect, loading dual cocatalysts, and coating stable shell. Special attention is paid to the influence mechanism of latest strategies on the photocatalytic process, with a focus on charge transfer, separation, and participation in surface chemical reaction behavior. Finally, with the goal of promoting the rapid progress of metal sulfides for solar hydrogen production, the key challenges of the latest research frontiers and the prospects on future development of metal sulfides are discussed.
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

The 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

The 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

Der 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

Im 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

Model 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

Adversarial 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

The 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

In 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

When 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

Artificial 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

This 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

Wheat 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

In 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

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

Recent 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.
Regularities of Pareto sets in low-dimensional practical multi-criteria optimisation problems: analysis, explanation, and exploitation
Authors: Kulkarni Aditya , Kohns Maximilian , Bortz Michael , Küfer Karl-Heinz , Hasse Hans
Published: July 2022

Many practical optimisation problems have conflicting objectives, which should be addressed by multi-criteria optimisation (MCO), i.e. by determining the set of best compromises, the Pareto set (PS), along with its picture in parameter space (PSPS). In previous work on low-dimensional MCO problems, we have found characteristic topological features of the PS and PSPS, which depend on the dimensionality of the parameter space M and the objective space N. E.g., $$M = 2$$

M
=
2

and $$N = 3$$

N
=
3

yields triangles with needle-like extensions. The reasons for these topological features were unknown so far. Here, we show that they are to be expected if all objective functions of the MCO satisfy two conditions: (a) they can be approximated by quadratic functions and (b) one of the eigenvalues of the Hessian matrix evaluated at the function’s minimum is small compared to the other eigenvalues. Objective functions which meet conditions (a) and (b) have a valley-like topology, for which the valley lies in the direction of the eigenvector corresponding to the lowest eigenvalue. The PSPS can be estimated by starting at the minimum of an objective function, following the valley, and combining these lines for all objective functions. The PS is obtained by evaluating the objective functions. We believe that the conditions (a) and (b) are met in many practical problems and discuss an example from molecular modelling. The improved understanding of the features of these MCO problems opens the route for designing methods for swiftly finding estimates of their PS and PSPS.
Veritism and ways of deriving epistemic value
Authors: Sjölin Wirling Ylwa
Published: July 2022

Veritists hold that only truth has fundamental epistemic value. They are committed to explaining all other instances of epistemic goodness as somehow deriving their value through a relation to truth, and in order to do so they arguably need a non-instrumental relation of epistemic value derivation. As is currently common in epistemology, many veritists assume that the epistemic is an insulated evaluative domain: claims about what has epistemic value are independent of claims about what has value simpliciter. This paper argues that the insulation approach to epistemic value is incompatible with non-instrumental epistemic value derivation. Veritsts who want to avail themselves of this important explanatory resource should therefore abandon the insulation approach.
Improving bounds on prime counting functions by partial verification of the Riemann hypothesis
Authors: Johnston Daniel R.
Published: July 2022

Using a recent verification of the Riemann hypothesis up to height $$3\cdot 10^{12}$$

3
·

10
12

, we provide strong estimates on $$\pi (x)$$

π
(
x
)

and other prime counting functions for finite ranges of x. In particular, we get that $$|\pi (x)-li(x)|<\sqrt{x}\log x/8\pi $$

|
π

(
x
)

-
l
i

(
x
)

|
<

x

log
x
/
8
π

for $$2657\le x\le 1.101\cdot 10^{26}$$

2657
≤
x
≤
1.101
·

10
26

. We also provide weaker bounds that hold for a wider range of x, and an application to an inequality of Ramanujan.
Impact factions: assessing the citation impact of different types of open access repositories
Authors: Wheeler Jonathan , Pham Ngoc-Minh , Arlitsch Kenning , Shanks Justin D.
Published: July 2022

Institutional repositories (IR) maintained by research libraries play a central role in providing open access to taxpayer-funded research products. It is difficult to measure the extent to which IR contribute to new scholarship because publisher self-archiving policies typically require researchers to cite the “version of record” of a manuscript even when an IR copy is accessed to conduct the research. While some studies report an open access (OA) citation advantage resulting from the availability of self-archived or “green” OA manuscripts, few have sought to measure an OA citation effect of IR separately from disciplinary repositories, including arXiv and PubMed Central. In this study, the authors present a bibliometric analysis examining correlations between search engine performance of items in IR, OA availability from different types of repositories, and citations. The analysis uses a novel, open dataset of IR access and usage derived from five months of Google search engine results pages (SERP) data, which were aggregated by the Repository Analytics and Metrics Portal (RAMP) web service. Findings indicate that making OA copies of manuscripts available in self-archiving or “green” repositories results in a positive citation effect, although the disciplinary repositories within the sample significantly outperform the other types of OA services analyzed. Also evident is an increase in citations when a single manuscript is available in multiple OA sources.
Epistemic anxiety and epistemic risk
Authors: Newton Lilith
Published: July 2022

In this paper, I provide an account of epistemic anxiety as an emotional response to epistemic risk: the risk of believing in error. The motivation for this account is threefold. First, it makes epistemic anxiety a species of anxiety, thus rendering psychologically respectable a notion that has heretofore been taken seriously only by epistemologists. Second, it illuminates the relationship between anxiety and risk. It is standard in psychology to conceive of anxiety as a response to risk, but psychologists – very reasonably – have little to say about risk itself, as opposed to risk judgement. In this paper, I specify what risk must be like to be the kind of thing to which anxiety can be a response. Third, my account improves on extant accounts of epistemic anxiety in the literature. It is more fleshed out than Jennifer Nagel’s (2010a), which is largely agnostic about the nature of epistemic anxiety, focusing instead on what work it does in our epistemic lives. In offering an account of epistemic anxiety as an emotion, my account explains how it is able to do the epistemological work to which Nagel puts it. My account is also more plausible than Juliette Vazard’s (2018, 2021), on which epistemic anxiety is an emotional response to potential threat to one’s practical interests. Vazard’s account cannot distinguish epistemic anxiety from anxiety in general, and also fails to capture all instances of what we want to call epistemic anxiety. My account does better on both counts.
The many theories of mind: eliminativism and pluralism in context
Authors: Gough Joe
Published: July 2022

In recent philosophy of science there has been much discussion of both pluralism, which embraces scientific terms with multiple meanings, and eliminativism, which rejects such terms. Some recent work focuses on the conditions that legitimize pluralism over eliminativism – the conditions under which such terms are acceptable. Often, this is understood as a matter of encouraging effective communication – the danger of these terms is thought to be equivocation, while the advantage is thought to be the fulfilment of ‘bridging roles’ that facilitate communication between different scientists and specialisms. These theories are geared towards regulating communication between scientists qua scientists. However, this overlooks an important class of harmful equivocation that involves miscommunication between scientists and nonscientists, such as the public or policymakers. To make my case, I use the example of theory of mind, also known as ‘mindreading’ and ‘mentalizing’, and broadly defined as the capacity to attribute mental states to oneself and others. I begin by showing that ‘theory of mind’ has multiple meanings, before showing that this has resulted in harmful equivocations of a sort and in a way not accounted for by previous theories of pluralism and eliminativism.
Angle of arrival estimation in a multi-antenna software defined radio system: impact of hardware and radio environment
Authors: Wachowiak Marcin , Kryszkiewicz Pawel
Published: July 2022

Contemporary wireless communication transceivers can utilize their multiple antennas to improve positioning abilities. Angle of Arrival (AoA) estimation utilizes shifts in phase between the signal of interest arriving at different receiving antennas. Software Defined Radio (SDR) USRP B210 and GNU Radio implementing the Root Multiple Signal Classification (Root-MUSIC) algorithm are used in this paper. However, this setup requires the consideration of errors caused by hardware and radio environment. The impact of these effects is shown using an analytical model, assessed, mostly by measurements, and relevant solutions are proposed. The hardware distortions are caused mostly by synchronization errors. The intricacies of the most problematic phase synchronization are investigated with the wired setup showing, e.g., changes with frequency or gain. Both synchronizations emitting calibration tone from the same radio front end, resulting in cross-talk, or a separate one are tested. Recommendations enhancing the performance of the system and alleviating hardware imperfections are provided in this paper. The accuracy of AoA estimation is degraded by multipath propagation or radio interference. A signal processing scheme including filtering has been proposed. A set of over-the-air experiments assessed the performance of the system. The presented and publicly available software package, scalable to a higher number of RX antennas, enables straightforward implementation by other researchers.
Reconstruction of dental roots for implant planning purposes: a feasibility study
Authors: Brandenburg Leonard Simon , Berger Lukas , Schwarz Steffen Jochen , Meine Hans , Weingart Julia Vera , Steybe David , Spies Benedikt Christopher , Burkhardt Felix , Schlager Stefan , Metzger Marc Christian
Published: July 2022

Purpose

Modern virtual implant planning is a time-consuming procedure, requiring a careful assessment of prosthetic and anatomical factors within a three-dimensional dataset. In order to facilitate the planning process and provide additional information, this study examines a statistical shape model (SSM) to compute the course of dental roots based on a surface scan.

Material and methods

Plaster models of orthognathic patients were scanned and superimposed with three-dimensional data of a cone-beam computer tomography (CBCT). Based on the open-source software “R”, including the packages Morpho, mesheR, Rvcg and RvtkStatismo, an SSM was generated to estimate the tooth axes. The accuracy of the calculated tooth axes was determined using a leave-one-out cross-validation. The deviation of tooth axis prediction in terms of angle or horizontal shift is described with mean and standard deviation. The planning dataset of an implant surgery patient was additionally analyzed using the SSM.

Results

71 datasets were included in this study. The mean angle between the estimated tooth-axis and the actual tooth-axis was 7.5 ± 4.3° in the upper jaw and 6.7 ± 3.8° in the lower jaw. The horizontal deviation between the tooth axis and estimated axis was 1.3 ± 0.8 mm close to the cementoenamel junction, and 0.7 ± 0.5 mm in the apical third of the root. Results for models with one missing tooth did not differ significantly. In the clinical dataset, the SSM could give a reasonable aid for implant positioning.

Conclusions

With the presented SSM, the approximate course of dental roots can be predicted based on a surface scan. There was no difference in predicting the tooth axis of existent or missing teeth. In clinical context, the estimation of tooth axes of missing teeth could serve as a reference for implant positioning. However, a higher number of training data must be achieved to obtain increasing accuracy.
Evaluating suitable low-cost agar substitutes, clarity, stability, and toxicity for resource-poor countries' tissue culture media
Authors: Ebile Pride Anya , Opata John , Hegele Suputtra
Published: July 2022

Over 20% of plant species assessed are threatened with extinction. Most of these plants have food security implications, especially in developing countries. Traditional seeds and cutting propagation techniques cannot counter the loss rate, and tissue culture provides a fast alternative to conventional propagation techniques. However, tissue culture has been considered too expensive for developing countries negatively impacted by food insecurity. A gelling agent is the costliest media component in plant tissue culture. This study aims to assess different gelling agents to find suitable ones with low cost and acceptable gelling properties for developing countries, especially in rural areas. Plantain explants were propagated on 16 starch-based substrates to evaluate their suitability as tissue culture gelling agents. This study compared the cost of various substrates and their gelling properties, such as clarity, toxicity, and texture, with agar as a reference gelling agent. Some substrates, such as xanthan, had good gelling properties, but their cost was too high (5.98 Euro L−1) to be considered low-cost. Other substrates, such as cassava starch, did not have suitable gelling properties; however, the cost was low (0.99 Euro L−1). Two of the substrates, mung bean and Isabgol, had suitable gelling properties and cost less than one euro. Therefore, smallholder banana and plantain farmers in resource-poor countries can undertake tissue culture operations with mung bean and Isabgol as gelling agents with minimum cost.
A State of the Art on Simulation and Modelling Methods in Machining: Future Prospects and Challenges
Authors: Korkmaz Mehmet Erdi , Gupta Munish Kumar
Published: July 2022

Simulation modelling methods have gained dramatic acceleration in the last years among academic environments and industry-driven enterprises. Primary reason is that such models have great potential in predicting of machining process parameters. Therefore, tis study evaluates the place and capability of these models in fundamental machining operations. In this direction, Finite Element Modelling Methods are discussed by questioning their contributions to the process performance. Despite numerous positive aspects, development of a successful model is highly difficult owing to the complexity of machining environment with variation of thermo-mechanical effect, tribological conditions, interaction of process variables and high deformation rate of materials etc. Therefore, a critical assessment of the merits and drawbacks of each method associating with their basic phenomena has been investigated. Predictive models basically aim to estimate the machinability characteristics such as stress–stain rates, cutting forces and temperatures etc. Nevertheless, practical applications require correlations between these characteristics and performance outcomes such as surface integrity of part, tool wear index, chip morphology, dimensional accuracy etc. In the end, the molecular dynamics and smoothed particle hydrodynamics have been discussed. Thus, this paper is expected to contribute to up-to-date studies by criticizing the key findings of the predictive models in machining processes.
Emotional States Encountered by Law Enforcement Officers: an Initial Test of the Schema Mode Concept in Police Actions
Authors: Deller-Wessels Lena , Bernstein David P. , Lorei Clemens
Published: July 2022

Working with extreme mood states is a regular challenge for law enforcement officers. In their encounters during police actions, they very often face manifestations of anger and aggression, as well as vulnerable states such as ones involving fear, helplessness, or humiliation. In this study, we investigated whether officers could reliably identify emotional states in the persons they encountered, using the Schema Therapy concept of “schema modes.” Although the mode concept has been extensively validated in the field of forensic mental health, this is its first application to police work. Twenty-seven police officers working for two different German police headquarters were asked to report about a recent operation involving a person showing intense emotional states. After receiving a short training in using the iModes, cards that facilitate working with modes, they retrospectively rated the presence and intensity of the schema modes of the persons whom they encountered. Two experts in Schema Therapy independently rated the same scenarios, using the Mode Observation Scale (MOS). Intraclass correlations showed moderate to excellent levels of agreement between the officers’ and experts’ mode-ratings. Modes involving anger (70%), aggression (70%), indirect hostility (44%), and arrogance/grandiosity (41%) were the most prevalent, while modes involving vulnerable emotions were less common. It can be concluded that police officers can reliably assess different modes in encountered persons, even without extensive training. This initial study suggests that the mode concept has applicability to police work and merits additional study for its potential for de-escalation and conflict management in police contexts.