Inaccessible Processes Research Articles

Multivalent Cartographic Accessibility: Tactile Maps for Collaborative Decision-Making

Conventional visual maps present significant accessibility challenges for blind or low vision users, leaving them with few or no options for interpreting spatial data. This need not be the case: tactile maps, designed to be read through touch, have been published for more than a century. But they have most often been categorized as a navigation tool, or mere “tactile graphics” (i.e., not as expressly spatial documents). Tactile maps that allow their users to explore and synthesize thematic spatial data are rare, as are studies evaluating them. As our world continues to face existential threats that are spatial in nature—pandemics, supply chain disruptions, floods, etc.—maps will continue to provide critical information in ways that other media are unable to match. In the absence of accessible thematic maps, blind people will not only be left out of the loop, but their capacity for contributing valuable input will be severely diminished. In response, I describe here a study that evaluates the potential of thematic tactile maps for providing blind users an accessible means of analyzing spatial data when working in collaboration with sighted partners. Findings indicate that while the maps did not prove to be useful tools on their own, they did facilitate collaboration between blind or low vision participants and sighted participants. This suggests that, with some refinements, similar maps could be feasibly distributed as a means for people with visual disabilities to meaningfully participate in an otherwise inaccessible process that requires the synthesis of thematic spatial information.

Activating charge-transfer state formation in strongly-coupled dimers using DNA scaffolds.

Strongly-coupled multichromophoric assemblies orchestrate the absorption, transport, and conversion of photonic energy in natural and synthetic systems. Programming these functionalities involves the production of materials in which chromophore placement is precisely controlled. DNA nanomaterials have emerged as a programmable scaffold that introduces the control necessary to select desired excitonic properties. While the ability to control photophysical processes, such as energy transport, has been established, similar control over photochemical processes, such as interchromophore charge transfer, has not been demonstrated in DNA. In particular, charge transfer requires the presence of close-range interchromophoric interactions, which have a particularly steep distance dependence, but are required for eventual energy conversion. Here, we report a DNA-chromophore platform in which long-range excitonic couplings and short-range charge-transfer couplings can be tailored. Using combinatorial screening, we discovered chromophore geometries that enhance or suppress photochemistry. We combined spectroscopic and computational results to establish the presence of symmetry-breaking charge transfer in DNA-scaffolded squaraines, which had not been previously achieved in these chromophores. Our results demonstrate that the geometric control introduced through the DNA can access otherwise inaccessible processes and program the evolution of excitonic states of molecular chromophores, opening up opportunities for designer photoactive materials for light harvesting and computation.

Methods of teaching inverse and incorrect problems to students in the context of informatization of education

Problem and goal. Computer technologies are now widely used in applied research aimed at obtaining new scientific knowledge. These studies used the method of computer modeling and computing experiment, from which it is possible to study the properties of remote or inaccessible objects, processes and phenomena of different nature. The above mentioned is directly related to teaching students applied mathematics in general, and, in particular, to teaching students of physical and mathematical training areas inverse and ill-posed problems, which are the scientific direction of applied mathematics. It is obvious that in the process of teaching students inverse and ill-posed problems, it is advisable to use computer technologies. However, the use of computer technology should be appropriate and correct. Methodology. The process of finding solutions to inverse and ill-posed problems is usually time-consuming, since such mathematical problems are non-linear in their formulation and may have a non-unique and unstable solution. These circumstances pose a mathematical difficulty in the proof of the theorems of existence, uniqueness and stability of solutions to inverse and ill-posed problems. Computer technologies help to overcome mathematical difficulties associated with routine transformations, analysis of information about solving such mathematical problems. Results. Using computer technologies, students gain experience in mobile research of various inverse and ill-posed problems, as well as in identifying the capabilities of computer technologies in solving various applied mathematical problems, and develop ICT competence. Conclusion. When using multimedia and computer technologies in the process of teaching students inverse and ill-posed problems, didactic principles of teaching are implemented, which allow students to acquire deep scientific knowledge on inverse and ill-posed problems, and develop their information culture.

Exact Coarse Graining Preserves Entropy Production out of Equilibrium.

The entropy production rate associated with broken time-reversal symmetry provides an essential characterization of nanosystems out of equilibrium, from driven colloidal particles to molecular motors. Limited access to the dynamical states is generally expected to hinder the correct estimation of this observable. Here we show how memoryless jump processes can be coarse grained, exactly preserving its average and fluctuations at stationarity. This supports univocal applicability of fluctuation theorems for entropy and allows inference of the genuine thermodynamics together with inaccessible process details.

Selective background Monte Carlo simulation at Belle II

The Belle II experiment, beginning data taking with the full detector in early 2019, is expected to produce a volume of data ffty times that of its predecessor. This dramatic increase in data comes the opportunity for studies of rare previously inaccessible processes. The investigation of such rare processes in a high data-volume environment requires a correspondingly high volume of Monte Carlo simulations to prepare analyses and gain a deep understanding of the contributing physics processes to each individual study. This presents a signifcant challenge in terms of computing resource requirements and calls for more intelligent methods of simulation, in particular background processes with very high rejection rates. This work presents a method of predicting in the early stages of the simulation process the likelihood of relevancy of an individual event to the target study using convolutional neural networks. The results show a robust training that is integrated natively into the existing Belle II analysis software framework.

Selective background Monte Carlo simulation at Belle II

The large volume of data expected to be produced by the Belle II experiment presents the opportunity for studies of rare, previously inaccessible processes. Investigating such rare processes in a high data volume environment necessitates a correspondingly high volume of Monte Carlo simulations to prepare analyses and gain a deep understanding of the contributing physics processes to each individual study. This resulting challenge, in terms of computing resource requirements, calls for more intelligent methods of simulation, in particular for processes with very high background rejection rates. This work presents a method of predicting in the early stages of the simulation process the likelihood of relevancy of an individual event to the target study using graph neural networks. The results show a robust training that is integrated natively into the existing Belle II analysis software framework.

Development of ICT competence among students when teaching inverse problems for differential equations with the use of computer technology

Problem and goal. The great need to apply the theory of inverse problems for differential equations (IP) in the research of applied problems is explained by the fact that it is possible to effectively study hard-to-reach or inaccessible objects and processes, to identify, for example, the location of objects, determine their shape, etc. In addition, it is possible to identify causeand-effect relationships of processes and phenomena (see, for example, [5; 6; 8; 11; 14; 17; 19]). It became possible, in many respects, thanks to modern computer technologies which allow to investigate various mathematical models of inverse problems, realize modern computational algorithms of the numerical solution of inverse problems for differential equations, carry out three-dimensional visualization of their decisions and control of accuracy of calculations. This circumstance explains the widespread introduction of modern computer technologies in the process of teaching students of IP educational institutions of physics and mathematics (see, for example, [2; 5; 6; 8; 10-14; 17; 19; 20]). In the process of teaching, goals are set to ensure that students form a system of fundamental knowledge in the field of theory and practice of inverse problems, applied and computational mathematics, acquire the skills to choose and apply computer technology to find solutions to inverse problems, develop their ICT competence. Methodology. The development of ICT competence among students of universities of physical and mathematical areas of training, as a result of learning IP, is ensured by how successfully the conditions will be implemented in practice, including: 1) involvement of specialists in the field of inverse problems for differential equations with experience in the use of computer technology in the study of inverse problems; 2) conducting lectures and practical classes using multimedia and computer technologies; 3) implementation of didactic principles of teaching inverse problems for differential equations using computer technologies; 4) attraction of students to performance of semester tasks, course and final qualifying works on inverse problems for differential equations with use of computer technologies. Results. In practical classes, students acquire the skills to apply modern computer technology in the study of IP. Students gain experience in analyzing new information about the studied physical processes and phenomena using computer technology. Students form knowledge about the role of computer technology in mobile research of mathematical models of inverse problems for differential equations, demonstrating ICT competence. Conclusion. Developed in the process of teaching inverse problems for differential equations using computer technologies, ICT competence will obviously allow students in their future professional activities to effectively apply a variety of computer technologies in the study of mathematical models of inverse problems.

How to Characterize Stem Cells? Contributions from Mathematical Modeling

Adult stem cells play a key role in tissue regeneration and cancer. To translate findings from stem cell biology into clinics, we require a quantitative characterization of stem cell dynamics in vivo. This review explores how mathematical models can help to characterize stem cell behavior in health and disease. Mathematical models significantly contribute to quantification of stem cell traits such as proliferation, self-renewal, and quiescence. They provide insights into the role of systemic and micro-environmental feedback loops during regeneration and cancer. Computer simulations allow linking stem cell properties to tumor composition, clinical course, and drug response. Therefore, models are helpful in personalizing treatments and predicting patient survival. Mathematical models coupled with tools of parameter estimation and model selection provide quantitative insights into stem cell properties and their regulation. They help to understand experimentally inaccessible processes occurring in regeneration, aging, and cancer.

Environmental impact assessment of biomass process chains at early design stages using decision trees

Life cycle assessment (LCA) is generally considered as a suitable methodology for the evaluation of environmental impacts of processes. However, it requires large amount and often inaccessible process data at early design stages. The present study provides an approach to streamline LCA for a broad set of biomass process chains. The proposed method breaks away from conventional LCA work in that the purpose is to support decision at early stages assuming minimal use of data available and points to most dominant LCA impacts, providing useful feedback to process design. The prediction mechanism employs decision trees, which form “if-then rules” using a set of critical parameters of the process chain with respect to various environmental impacts. The models classify products into three classes, namely having low, medium, and high environmental impact. Data for model development were obtained from early design stages and include descriptors of the molecular structure of the product and process chain-related variables corresponding to chemistry, complexity, and generic process conditions. Twenty-three LCA metrics were selected as target attributes, according to the ReCiPe and the cumulative energy demand (CED) methods. A broad set of process chains is derived from the work of Karka et al. (Int J Life Cycle Assess 22(9):1418–1440, 2017). Results demonstrate that the average classification error for the decision trees ranges between 13.4 and 43.8% for the various LCA metrics and multifunctionality approaches. Allocation approaches present a better classification performance (up to 25% error) compared with the substitution approach for LCA metrics, such as climate change, CED, and human health. For the majority of models, low- and high-output classes are characterized by better predictive performance compared with the medium class. The interpretability of selected decision trees is analyzed in terms of pruning levels and “irrational” branches. The results of the application of the decision tress for recently published case studies show for instance that 8 out of 13 cases were correctly classified for CED. The proposed approach provides a first generation of models in the form of computationally inexpensive and easily interpretable decision trees that can be used as pre-screening tools for the environmental assessment of bio-based production ahead of detailed design and conventional LCA approaches. The transparent structure of the decision trees facilitates the identification of critical decision variables providing insights for improvement in terms of process parameters, biomass feedstock, or even targeted product.

A New Non-Equilibrium Thermodynamic Fractional Visco-Inelastic Model to Predict Experimentally Inaccessible Processes and Investigate Pathophysiological Cellular Structures

After remarking on non-equilibrium thermodynamics with internal variables, this paper highlights the importance of these variables to the study of biological systems. Internal variables can provide a more detailed description of biological processes that occur inside cells, tissues and organs. In order to introduce a fractional model on a visco-inelastic medium based on Kluitenberg’s non-equilibrium thermodynamics, the origin of the complex dynamic modulus is shown by means of linear response theory. This research recalls our previous work to develop an ultrasound wave technique that allows us to investigate biological systems, and introduces the fractional visco-inelastic model and relative generalized relaxation time, to show that it is possible to obtain the Cole–Cole model in a particular case.

Earthquake swarms reveal submarine magma unrest induced by distant mega-earthquakes: Andaman Sea region

Little is known about earthquake-triggered magma intrusions or eruptions of submarine volcanoes. The analysis of teleseismic earthquake occurrence performed in this study offers a tool to address such enigmatic and inaccessible processes. In the past ten years, the Andaman Sea region repeatedly became a site of shallow earthquake swarms that followed distant mega-earthquakes by days to weeks. The MW 9.1 December 26, 2004 Sumatra–Andaman earthquake was followed by two earthquake swarms about 600km northward in the Andaman Sea region, delayed by 30 and 35days, respectively. Earthquakes of one of these seismic episodes, the extensive January 2005 earthquake swarm, migrated laterally at a rate of about 0.25km per hour during the swarm evolution. The strong Indian Ocean MW 8.6 and 8.2 April 11, 2012 earthquake doublet west of Northern Sumatra was followed by an earthquake swarm approximately 800km northward in the Andaman Sea region, delayed by 13days. All the three swarms that followed the 2004 and 2012 mega-earthquakes occurred beneath distinct seamounts and seafloor ridges. Based on the observations of migration of earthquakes during the swarm and swarm occurrence beneath distinct highs at the seafloor, we conclude that these earthquake swarms probably resulted as a consequence of magma unrest induced by static and/or dynamic stress changes following the distant mega-earthquakes. Repeated occurrence of such a phenomenon suggests that the arc magma reservoirs beneath the Andaman Sea have recently reached some form of criticality and are vulnerable to even small stress changes. The Andaman seafloor could thus become a site of submarine volcanic eruptions in near future and deserves close attention of Earth scientists.

Measuring the Inaccessible Earth: Geomagnetism, In situ Measurements, Remote Sensing, and Proxy Data

The usual problems of measurement and its meaning are complicated and magnified when the object of study is in principle and in fact inaccessible. When a phenomenon occurs in a place where our instruments cannot reach, what can the relation between the instrument, its reading, and the phenomenon be? This essay asks how researchers have addressed questions about inaccessible processes of Earth's magnetic field on the surface, at the edge of space and under its surface. This case takes us beyond simple contrasts of inductive and deductive methods, or field sciences versus basic sciences, to a messier, more nuanced view of inherently complex sciences. The article focuses on investigations of Earth's magnetism and electricity, but its perspectives are applicable to many areas of recent science.

Systems biology and biomarker discovery.

Medical practitioners have always relied on surrogate markers of inaccessible biological processes to make their diagnosis, whether it was the pallor of shock, the flush of inflammation, or the jaundice of liver failure. Obviously, the current implementation of biomarkers for disease is far more sophisticated, relying on highly reproducible, quantitative measurements of molecules that are often mechanistically associated with the disease in question, as in glycated hemoglobin for the diagnosis of diabetes [1] or the presence of cardiac troponins in the blood for confirmation of myocardial infarcts [2]. In cancer, where the initial symptoms are often subtle and the consequences of delayed diagnosis often drastic for disease management, the impetus to discover readily accessible, reliable, and accurate biomarkers for early detection is compelling. Yet despite years of intense activity, the stable of clinically validated, cost-effective biomarkers for early detection of cancer is pathetically small and still dominated by a handful of markers (CA-125, CEA, PSA) first discovered decades ago. It is time, one could argue, for a fresh approach to the discovery and validation of disease biomarkers, one that takes full advantage of the revolution in genomic technologies and in the development of computational tools for the analysis of largemore » complex datasets. This issue of Disease Markers is dedicated to one such new approach, loosely termed the 'Systems Biology of Biomarkers'. What sets the Systems Biology approach apart from other, more traditional approaches, is both the types of data used, and the tools used for data analysis - and both reflect the revolution in high throughput analytical methods and high throughput computing that has characterized the start of the twenty first century.« less

Morality on the Web

PSYCHOLOGY Inconsistencies—for instance, between what is observed and what is reported—can be fecund ground for researchers to till, and a topic of current interest is the incongruence between the moral judgments that people make and the reasons that people proffer as a basis for those judgments. At one side are the proponents of conscious or deliberative thought as the means for making choices when confronted with moral dilemmas, whereas another view favors intuitions arrived at via automatic or inaccessible processes as the motivation for their responses. Cushman et al. have elicited “ought versus ought not” judgments and postjudgment rationales from more than 500 people by using a Web-based script. Participants read carefully constructed scenarios and registered their judgments; they were then presented with their choices in pairs of the scenarios that differed in only one of three dimensions and asked for a justification. In situations where action (or inaction) was involved, participants were consistent in their judgments and generally had no difficulty in articulating a reasoned argument for how they had decided which behavior was morally better. In contrast, when intentional (or unintentional) harm was the issue, the pattern of judgment was just as clear as in the action scenarios, but most participants could not explain why they had chosen as they did. Hence, there may be more than one way to reach a decision on morality. — GJC Psychol. Sci. 17 , 1082 (2006).

A Latent State-Trait Analysis of Implicit and Explicit Personality Measures

Abstract. Explicit personality measures assess introspectively accessible self-descriptions. In contrast, implicit personality measures assess introspectively inaccessible processes that operate outside awareness. However, for both kinds of trait measures, the effect of the situation in which the assessment takes place should be as small as possible. The present study aims at quantifying possible systematic occasion-specific effects on implicit measures (Implicit Association Test) and explicit measures (self-report ratings) of extraversion and anxiety by means of a latent state-trait analysis. This analysis revealed that - as desired for personality assessment - all four measures capture mostly stable interindividual differences. Nevertheless, occasion-specific effects were also observed. These effects were (1) more pronounced for implicit than for explicit measures and (2) more pronounced for anxiety than for extraversion. Implications for the implicit assessment of personality traits are discussed.

Gender differences in implicit and explicit anxiety measures

Abstract Explicit measures assess introspectively accessible self-descriptions and evaluations. In contrast, implicit measures assess introspectively inaccessible processes that operate outside of awareness. While women consistently yield higher scores on explicit anxiety measures, there are to date no studies available that examine gender differences in implicit anxiety measures. To analyse this topic, we used the Implicit Association Test (Study 1, N =248) and the Emotional Stroop task (Study 2, N =121) as implicit anxiety measures and a standard trait questionnaire as explicit anxiety measure. As expected, women scored higher on the explicit anxiety test. Women also yielded higher anxiety scores on both implicit tests. The effect sizes of the gender differences in the implicit measures were approximately half as large as those in the explicit measures. Furthermore, correlations between implicit and explicit measures were higher for women. Implications of these findings for personality assessment are discussed.

Does social desirability moderate the relationship between implicit and explicit anxiety measures?

Abstract Explicit measures assess introspectively accessible self-descriptions and evaluations. In contrast, implicit measures assess introspectively inaccessible processes that operate outside of awareness. Consequently, implicit measures should be free of response factors such as faking tendencies and social desirability (SD). Usually, correlations between implicit and explicit measures of the same construct tend to be low. Study 1 (N=145) tested the hypothesis that SD should moderate the relationship between an implicit (the Implicit Association Test) and an explicit (a standard questionnaire) anxiety measure. Study 2 (N=62) extended this test by distinguishing between the SD components of self-deceptive enhancement and impression management. However, results of both studies suggest that SD does not act as a moderator between implicit and explicit anxiety measures. The discussion focuses on implications and limitations of this finding.

Short-term synaptic plasticity, simulation of nerve terminal dynamics, and the effects of protein kinase C activation in rat hippocampus.

Phorbol esters are hypothesised to produce a protein kinase C (PKC)-dependent increase in the probability of transmitter release via two mechanisms: facilitation of vesicle fusion or increases in synaptic vesicle number and replenishment. We used a combination of electrophysiology and computer simulation to distinguish these possibilities. We constructed a stochastic model of the presynaptic contacts between a pair of hippocampal pyramidal cells that used biologically realistic processes and was constrained by electrophysiological data. The model reproduced faithfully several forms of short-term synaptic plasticity, including short-term synaptic depression (STD), and allowed us to manipulate several experimentally inaccessible processes. Simulation of an increase in the size of the readily releasable vesicle pool and the time of vesicle replenishment decreased STD, whereas simulation of a facilitation of vesicle fusion downstream of Ca(2+) influx enhanced STD. Because activation of protein kinase C with phorbol ester enhanced STD of EPSCs in rat hippocampal slice cultures, we conclude that an increase in the sensitivity of the release process for Ca(2+) underlies the potentiation of neurotransmitter release by PKC.

Implicit anxiety measure predicts cardiovascular reactivity to an evaluated speaking task.

Explicit personality tests assess introspectively accessible self-descriptions. By contrast, implicit personality tests assess introspectively inaccessible processes that operate outside of awareness. Despite their inaccessibility, implicit processes are presumed to influence a variety of current responses. This study tested the hypothesis that an implicit anxiety test should predict cardiovascular reactivity during a speech stressor task. In all, 97 participants completed a measure of attention allocation toward threat (implicit test) and an anxiety questionnaire (explicit test) 1 week before giving an evaluated speech. Whereas the explicit test showed modest relations within only 1 measure of cardiovascular reactivity, the implicit test predicted heart rate and blood pressure reactivity during preparation and delivery of the speech. These findings encourage the broader use of implicit measures to assess cardiovascular responses to threat.

Object components for comminution system softsensor design

Over the last decade or so, a new “softsensor” technology has been evolving which permits previously inaccessible process variables to be estimated. The “softsensor” is a piece of software which processes inputs from instruments that provide information related to the unknown variables and interprets these in the context of an on-line model to arrive at the “best available” estimate of the unknown variable(s). Using as a starting point some early work conducted at the University of Utah and GS Industries, the authors describe in the current paper a general object-oriented approach to the design of softsensors for comminution systems. A generic softsensor, ComMINSens, is shown to be integrable with a variety of models in the form of object components. Applications are presented for SAG milling and ball milling circuits.