342 research outputs found
Thermal and structural properties of ionic fluids
The electrostatic interaction in ionic fluids is well-known to give rise to a
characteristic phase behavior and structure. Sometimes its long range is
proposed to single out the electrostatic potential over other interactions with
shorter ranges. Here the importance of the range for the phase behavior and the
structure of ionic fluids is investigated by means of grandcanonical Monte
Carlo simulations of the lattice restricted primitive model (LRPM). The
long-ranged electrostatic interaction is compared to various types of
short-ranged potentials obtained by sharp and/or smooth cut-off schemes.
Sharply cut off electrostatic potentials are found to lead to a strong
dependence of the phase behavior and the structure on the cut-off radius.
However, when combined with a suitable additional smooth cut-off, the
short-ranged LRPM is found to exhibit quantitatively the same phase behavior
and structure as the conventional long-ranged LRPM. Moreover, the
Stillinger-Lovett perfect screening property, which is well-known to be
generated by the long-ranged electrostatic potential, is also fulfilled by
short-ranged LRPMs with smooth cut-offs. By showing that the characteristic
phase behavior and structure of ionic fluids can also be found in systems with
short-ranged potentials, one can conclude that the decisive property of the
electrostatic potential in ionic fluids is not the long range but rather the
valency dependence
Smectic phases in ionic liquid crystals
Ionic liquid crystals (ILCs) are anisotropic mesogenic molecules which carry
charges and therefore combine properties of liquid crystals, e.g., the
formation of mesophases, and of ionic liquids, such as low melting temperatures
and tiny triple-point pressures. Previous density functional calculations have
revealed that the phase behavior of ILCs is strongly affected by their
molecular properties, i.e., their aspect ratio, the loci of the charges, and
their interaction strengths. Here, we report new findings concerning the phase
behavior of ILCs as obtained by density functional theory and Monte Carlo
simulations. The most important result is the occurrence of a novel, wide
smectic-A phase , at low temperature, the layer spacing of which is
larger than that of the ordinary high-temperature smectic-A phase .
Unlike the ordinary smectic phase, the structure of the phase
consists of alternating layers of particles oriented parallel to the layer
normal and oriented perpendicular to it
Give me 3W1H: A Bibliometric View on Accountable AI
Accountability is crucial to make stakeholders of Artificial Intelligence (AI)-based systems justify their actions, thereby explaining the harm such systems cause to AI users. Due to the importance of accountability in the context of AI, accountability was introduced into IS research through literature reviews. Therefore, while IS research’s understanding of accountability covers the necessary depth, it comes at the expense of its essential breadth. Using a bibliometric analysis with 19,978 English-language papers, we shed light on the essential breadth posing three W- and one H-questions (When, What, Whereof, and How). Therefore, we contribute to IS research by highlighting the urgent need to revise existing definitions of accountability in the context of AI and establish them in IS research. We argue that a missing revision leads to non-transferrable findings within IS research. Accordingly, this study serves as a starting point for adapting definitions and creating a shared understanding in IS research
How AI Developers’ Perceived Accountability Shapes Their AI Design Decisions
While designing artificial intelligence (AI)-based systems, AI developers usually have to justify their design decisions and, thus, are accountable for their actions and how they design AI-based systems. Crucial facets of AI (i.e., autonomy, inscrutability, and learning) notably cause potential accountability issues that AI developers must consider in their design decisions, which has received little attention in prior literature. Drawing on self-determination theory and accountability literature, we conducted a scenario-based survey (n=132). We show that AI developers who perceive themselves as accountable tend to design AI-based systems to be less autonomous and inscrutable but more capable of learning when deployed. Our mediation analyses suggest that perceived job autonomy can partially explain these direct effects. Therefore, AI design decisions depend on individual and organizational settings and must be considered from different perspectives. Thus, we contribute to a better understanding of the effects of AI developers’ perceived accountability when designing AI-based systems
Interface structures in ionic liquid crystals
Ionic liquid crystals (ILCs) are anisotropic mesogenic molecules which
additionally carry charges. This combination gives rise to a complex interplay
of the underlying (anisotropic) contributions to the pair interactions. It
promises interesting and distinctive structural and orientational properties to
arise in systems of ILCs, combining properties of liquid crystals and ionic
liquids. While previous theoretical studies have focused on the phase behavior
of ILCs and the structure of the respective bulk phases, in the present study
we provide new results, obtained within density functional theory, concerning
(planar) free interfaces between an isotropic liquid and two types of
smectic-A phases ( or ). We discuss the structural and
orientational properties of these interfaces in terms of the packing fraction
profile and the orientational order parameter profile
concerning the tilt angle between the (bulk) smectic
layer normal and the interface normal. The asymptotic decay of
and of towards their values in the isotropic bulk is discussed,
too
The Role of Process and Outcome Accountability Claims for Shaping AI Developers’ Perceived Accountability
As accountability becomes increasingly important for developers of artificial intelligence (AI)-based systems, governance mechanisms such as AI principles or audits are often criticized for not sufficiently influencing AI developers. Therefore, we examine how visualized arguments in user interfaces (UIs) of integrated development environments (IDEs) can increase AI developers’ perceived accountability. Combining construal level theory and Toulmin’s model of argumentation, four UI design artifacts were developed, each containing a claim of process or outcome accountability with or without monitoring and evaluation tools that act as claim-supporting data. Results of an online experiment with 164 AI developers show that claiming process accountability increases AI developers’ perceived accountability more than claiming outcome accountability, both without supporting data. However, when supporting data are available, both claims increase AI developers’ perceived accountability comparably effectively. The study’s results highlight the theoretical and practical usefulness of visualized arguments in UIs of IDEs to promote AI developers’ accountability
ACCOUNTABILITY INCONGRUENCE AND ITS EFFECTS ON AI DEVELOPERS’ JOB SATISFACTION
Developers of Artificial Intelligence (AI)-based systems are increasingly urged to assume accountability for their development decisions, referring to the degree to which they must justify underlying algorithms and their outcomes on demand. Thereby, AI developers often have to juxtapose how much accountability they self-attribute to them and how much accountability they perceive others attribute to them, creating intrapersonal perceptual accountability (in)congruence with unknown consequences for their job satisfaction. Building on perceptual congruence research and algorithmic accountability literature, we conducted an online survey of 87 AI developers about their experiences in AI-based systems development projects. Our results show that the lower the incongruence between self-attributed and others-attributed accountability, the higher the job satisfaction of AI developers. Moreover, we find that AI developers’ role ambiguity mediates this effect. Our study contributes to a more nuanced understanding of AI developers’ perceived accountability, with essential insights for defining job roles and understanding AI developers
Video survey of deep benthic macroalgae and macroalgal detritus along a glacial Arctic fjord: Kongsfjorden (Spitsbergen)
In Kongsfjorden (Spitsbergen), we quantified the zonation of visually dominant macroalgal taxa and of detached macroalgae from underwater videos taken in summer 2009 at six transects between 2 and 138 m water depth. For the first time, we provide information on the occurrence of deep water red algae below the kelp forest and of detached macroalgae at water depth > 30 m. The presence and depth distribution of visually dominant red algae were especially pronounced at the outer fjord, decreased with proximity to the glacial front and they were absent at the innermost locations. Deepest crustose coralline red algae and foliose red algae were observed at 72 and 68 m, respectively. Brown algae were distributed along the entire fjord axis at 2–32 m. Green algae were only present at the middle to inner fjord and at areas influenced by physical disturbance at water depths of 2–26 m. With proximity to the inner fjord the depth distribution of all macroalgae became shallower and only extended to 18 m depth at the innermost location. Major recipients of detached macroalgae were sites at the shallower inner fjord and at the middle fjord below the photic zone at depths to 138 m. They may either fuel deep water secondary production, decompose or support carbon sequestration. Univariate and community analyses of macroalgal classes including detached macroalgae across transects and over depths reveal a considerable difference in community structure between the outermost sites, the central part and the inner fjord areas, reflecting the strong environmental gradients along glacial fjords
Video survey of deep benthic macroalgae and macroalgal detritus along a glacial Arctic fjord: Kongsfjorden (Spitsbergen)
In Kongsfjorden (Spitsbergen), we quantified the zonation of visually dominant macroalgal taxa and of detached macroalgae from underwater videos taken in summer 2009 at six transects between 2 and 138 m water depth. For the first time, we provide information on the occurrence of deep water red algae below the kelp forest and of detached macroalgae at water depth > 30 m. The presence and depth distribution of visually dominant red algae were especially pronounced at the outer fjord, decreased with proximity to the glacial front and they were absent at the innermost locations. Deepest crustose coralline red algae and foliose red algae were observed at 72 and 68 m, respectively. Brown algae were distributed along the entire fjord axis at 2–32 m. Green algae were only present at the middle to inner fjord and at areas influenced by physical disturbance at water depths of 2–26 m. With proximity to the inner fjord the depth distribution of all macroalgae became shallower and only extended to 18 m depth at the innermost location. Major recipients of detached macroalgae were sites at the shallower inner fjord and at the middle fjord below the photic zone at depths to 138 m. They may either fuel deep water secondary production, decompose or support carbon sequestration. Univariate and community analyses of macroalgal classes including detached macroalgae across transects and over depths reveal a considerable difference in community structure between the outermost sites, the central part and the inner fjord areas, reflecting the strong environmental gradients along glacial fjords
Structure-Function Correlation of the Human Central Retina
The impact of retinal pathology detected by high-resolution imaging on vision remains largely unexplored. Therefore, the aim of the study was to achieve high-resolution structure-function correlation of the human macula in vivo.To obtain high-resolution tomographic and topographic images of the macula spectral-domain optical coherence tomography (SD-OCT) and confocal scanning laser ophthalmoscopy (cSLO), respectively, were used. Functional mapping of the macula was obtained by using fundus-controlled microperimetry. Custom software allowed for co-registration of the fundus mapped microperimetry coordinates with both SD-OCT and cSLO datasets. The method was applied in a cross-sectional observational study of retinal diseases and in a clinical trial investigating the effectiveness of intravitreal ranibizumab in macular telangietasia type 2. There was a significant relationship between outer retinal thickness and retinal sensitivity (p<0.001) and neurodegeneration leaving less than about 50 µm of parafoveal outer retinal thickness completely abolished light sensitivity. In contrast, functional preservation was found if neurodegeneration spared the photoreceptors, but caused quite extensive disruption of the inner retina. Longitudinal data revealed that small lesions affecting the photoreceptor layer typically precede functional detection but later cause severe loss of light sensitivity. Ranibizumab was shown to be ineffective to prevent such functional loss in macular telangietasia type 2.Since there is a general need for efficient monitoring of the effectiveness of therapy in neurodegenerative diseases of the retina and since SD-OCT imaging is becoming more widely available, surrogate endpoints derived from such structure-function correlation may become highly relevant in future clinical trials
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