Miracle-dz/UniFAR-FTUs huggingface dataset:
Exotic dynamics in a firing rate model of neural tissue with threshold accommodation

Many of the equations describing the dynamics of neural systems are written in terms of firing rate functions, which themselves are often taken to be threshold functions of synaptic activity. Dating back to work by Hill in 1936 it has been recognized that more realistic models of neural tissue can be obtained with the introduction of state-dependent dynamic thresholds. In this paper we treat a specific phenomenological model of threshold accommodation that mimics many of the properties originally described by Hill. Importantly we explore the consequences of this dynamic threshold at the tissue level, by modifying a standard neural field model of Wilson-Cowan type. As in the case without threshold accommodation classical Mexican-Hat connectivity is shown to allow for the existence of spatially localized states (bumps) in both one and two dimensions. Importantly an analysis of bump stability in one dimension, using recent Evans function techniques, shows that bumps may undergo instabilities leading to the emergence of both breathers and traveling waves. Moreover, a similar analysis for traveling pulses leads to the conditions necessary to observe a stable traveling breather. In the regime where a bump solution does not exist direct numerical simulations show the possibility of self-replicating bumps via a form of bump splitting. Simulations in two space dimensions show analogous localized and traveling solutions to those seen in one dimension. Indeed dynamical behavior in this neural model appears reminiscent of that seen in other dissipative systems that support localized structures, and in particular those of coupled cubic complex Ginzburg-Landau equations. Further numerical explorations illustrate that the traveling pulses in this model exhibit particle like properties, similar to those of dispersive solitons observed in some three component reaction-diffusion systems. A preliminary account of this work first appeared in S Coombes and M R Owen, Bumps, breathers, and waves in a neural network with spike frequency adaptation, Physical Review Letters 94 (2005), 148102(1-4).
Effect of Hygrothermal Aging on the Mechanical Properties of Fluorinated and Nonfluorinated Clay-Epoxy Nanocomposites

Hydrophilic nature of epoxy polymers can lead to both reversible and irreversible/permanent changes in epoxy upon moisture absorption. The permanent changes leading to the degradation of mechanical properties due to combined effect of moisture and elevated temperature on EPON 862, Nanomer I.28E, and Somasif MAE clay-epoxy nanocomposites are investigated in this study. The extent of permanent degradation on fracture and flexural properties due to the hygrothermal aging is determined by drying the epoxy and their clay-epoxy nanocomposites after moisture absorption. Significant permanent damage is observed for fracture toughness and flexural modulus, while the extent of permanent damage is less significant for flexural strength. It is also observed that permanent degradation in Somasif MAE clay-epoxy nanocomposites is higher compared to Nanomer I.28E clay-epoxy nanocomposites. Fourier transform infrared (FTIR) spectroscopy revealed that both clays retained their original chemical structure after the absorption-desorption cycle without undergoing significant changes. Scanning electron microscopy (SEM) images of the fracture surfaces provide evidence that Somasif MAE clay particles offered very little resistance to crack propagation in case of redried specimens when compared to Nanomer I.28E counterpart. The reason for the observed higher extent of permanent degradation in Somasif MAE clay-epoxy system has been attributed to the weakening of the filler-matrix interface.
Clinical proteomics in kidney disease as an exponential technology: heading towards the disruptive phase

Abstract Exponential technologies double in power or processing speed every year, whereas their cost halves. Deception and disruption are two key stages in the development of exponential technologies. Deception occurs when, after initial introduction, technologies are dismissed as irrelevant, while they continue to progress, perhaps not as fast or with so many immediate practical applications as initially thought. Twenty years after the first publications, clinical proteomics is still not available in most hospitals and some clinicians have felt deception at unfulfilled promises. However, there are indications that clinical proteomics may be entering the disruptive phase, where, once refined, technologies disrupt established industries or procedures. In this regard, recent manuscripts in CKJ illustrate how proteomics is entering the clinical realm, with applications ranging from the identification of amyloid proteins in the pathology lab, to a new generation of urinary biomarkers for chronic kidney disease (CKD) assessment and outcome prediction. Indeed, one such panel of urinary peptidomics biomarkers, CKD273, recently received a Food and Drug Administration letter of support, the first ever in the CKD field. In addition, a must-read resource providing information on kidney disease-related proteomics and systems biology databases and how to access and use them in clinical decision-making was also recently published in CKJ.
Exploring clinical best practices for working with the co-occurrence of psychosis and a trauma history

This qualitative research study explored clinical practices most effective in helping people who experience co-occurring psychosis and a trauma history. The research was conducted through interviews with nine mental health professionals, who reported they created their own skill base in working with clients with a co-occurrence of psychosis and trauma. Although every respondent reported this co-occurrence as common, they all expressed a lack of confidence and expertise in treating the population. Best practices for treatment were found to be a combination of psychiatric medication, psychotherapy, and community support. Themes of treatment included the need to establish trusting relationships, appreciate client strengths, and support clients in making meaning of their experiences. Practices reported as helpful for treating psychosis were sometimes considered contraindicated for trauma. Respondents identified increased tolerance for strong emotion and an expanded capacity for self-care as positive outcomes for their clients, and treatment goals focused on quality of life. EXPLORING CLINICAL BEST PRACTICES FOR WORKING WITH THE CO-OCCURRENCE OF PSYCHOSIS AND A TRAUMA HISTORY A project based upon an independent investigation, submitted in partial fulfillment of the requirements for the degree of Master of Social Work.
Laser ranging: a critical review of usual techniques for distance measurement

We review some usual laser range finding techniques for in- dustrial applications. After outlining the basic principles of triangulation and time of flight (pulsed, phase-shift and frequency modulated continu- ous wave (FMCW)), we discuss their respective fundamental limitations. Selected examples of traditional and new applications are also briefly presented. © 2001 Society of Photo-Optical Instrumentation Engineers.
Test Quality Feedback Improving Effectivity and Efficiency of Unit Testing

Writing unit tests for a software system enhances the confidence that a system works as expected. Since time pressure often prevents a complete testing of all application details developers need to know which new tests the system requires. Developers also need to know which existing tests take the most time and slow down the whole development process. Missing feedback about less tested functionality and reasons for long running test cases make it, however, harder to create a test suite that covers all important parts of a software system in a minimum of time. As a result a software system may be inadequately tested and developers may test less frequently. Our approach provides test quality feedback to guide developers in identifying missing tests and correcting low-quality tests. We provide developers with a tool that analyzes test suites with respect to their effectivity (e.g., missing tests) and efficiency (e.g., time and memory consumption). We implement our approach, named Path Map, as an extended test runner within the Squeak Smalltalk IDE and demonstrate its benefits by improving the test quality of representative software systems.
Error Propagation Analysis for Quantitative Intracellular Metabolomics

Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The total measurement error of any analytical protocol is the result of an accumulation of single errors introduced by several processing steps. Here, we present a framework for the quantification of intracellular metabolites, including error propagation during metabolome sample processing. Focusing on one specific protocol, we comprehensively investigate all currently known and accessible factors that ultimately impact the accuracy of intracellular metabolite concentration data. All intermediate steps are modeled, and their uncertainty with respect to the final concentration data is rigorously quantified. Finally, on the basis of a comprehensive metabolome dataset of Corynebacterium glutamicum, an integrated error propagation analysis for all parts of the model is conducted, and the most critical steps for intracellular metabolite quantification are detected.
A longitudinal study of information system threat categories: the enduring problem of human error

Taxonomies of information security threats usually distinguish between accidental and intentional sources of system risk. Security reports have paid a great deal of attention in recent years to the growing problem of hacking and intentional abuse. The prevalence of these reports suggests that hacking has become a more severe problem in relation to other security threats, such as human error. In this paper, we report on research that addresses this question: "How have changes over time in the frequency of hacking and other intentional forms of security threats affected the validity of information systems risk management taxonomies? " We replicate a simple study of the proportions of categories of security threats that was originally completed in 1993. Comparing the results from the replicated study with the results from the original study, we find that the proportions of threat categories have, in contradiction with the popular perception, remained relatively stable over the past decade. These results indicate that human error remains a significant and poorly recognized issue for information systems security. We propose and validate an elaborated taxonomy of information security threats that provides additional insight into human error as a significant source of security risk.
Architectural Complexity Measures of Recurrent Neural Networks

In this paper, we systematically analyze the connecting architectures of recurrent neural networks (RNNs). Our main contribution is twofold: first, we present a rigorous graph-theoretic framework describing the connecting architectures of RNNs in general. Second, we propose three architecture complexity measures of RNNs: (a) the recurrent depth, which captures the RNN's over-time nonlinear complexity, (b) the feedforward depth, which captures the local input-output nonlinearity (similar to the "depth" in feedforward neural networks (FNNs)), and (c) the recurrent skip coefficient which captures how rapidly the information propagates over time. We rigorously prove each measure's existence and computability. Our experimental results show that RNNs might benefit from larger recurrent depth and feedforward depth. We further demonstrate that increasing recurrent skip coefficient offers performance boosts on long term dependency problems.
A qualitative exploration of evidence-based decision making in public health practice and policy: the perceived usefulness of a diabetes economic model for decision makers

Purpose The purpose of this paper is to explore the perceived usefulness of a diabetes economic model as a potential tool for aiding evidence-based decision making in public health. Methods Fifteen interviews and two focus groups, with four participants in each, were conducted with health and management professionals working in one public health department in a local council. Data were analysed using inductive thematic analysis to generate four themes. Findings The findings reflect attitudes and beliefs of a diverse staff group situated in public health services. Findings reveal that the economic model was perceived as useful and participants reported positive views regarding the principles of economic modelling for decision making. However, it was potentially problematic in practice due to organisational constraints linked to limited resources, restricted budgets and local priorities. Differences in institutional logics of staff working across public health and local government departments were identified as a potential barrier to the use of the model in practice. Discussion The findings highlight anticipated challenges that public health practice and policy decision-makers could face if they selected to implement an economic modelling approach to fulfil their evidence needs. Previous studies have revealed that healthcare decision makers would find evidence around the economic impacts of public health interventions useful, but this information was not always available in the format required. This paper provides insights into how public health staff perceive economic modelling, and explores how they use this type of evidence when making public health practice and policy decisions.
Reading between the lines of failure logs: Understanding how HPC systems fail

As the component count in supercomputing installations continues to increase, system reliability is becoming one of the major issues in designing HPC systems. These issues will become more challenging in future Exascale systems, which are predicted to include millions of CPU cores. Even with relatively reliable individual components, the sheer number of components will increase failure rates to unprecedented levels. Efficiently running those systems will require a good understanding of how different factors impact system reliability. In this paper we use a decade worth of field data made available by Los Alamos National Lab to study the impact of a diverse set of factors on the reliability of HPC systems. We provide insights into the nature of correlations between failures, and investigate the impact of factors, such as the power quality, temperature, fan and chiller reliability, system usage and utilization, and external factors, such as cosmic radiation, on system reliability.
Representing Mental Events (or the Lack Thereof)

This paper focusses upon the level of granularity at which representations for the mental world should be placed. That is, if one wishes to represent thinking about the self, about the states and processes of reasoning, at what level of detail should one attempt to declaratively capture the contents of thought? Some claim that a mere set of two mental primitives are sufficient to represent the utterances of humans concerning verbs of thought such as "I forgot her name. " Alternatively, many in the artificial intelligence community have built systems that record elaborate traces of reasoning, keep track of knowledge dependencies or inference, or encode much metaknowledge concerning the structure of internal rules and defaults. The position here is that the overhead involved with a complete trace of mental behavior and knowledge structures is intractable and does not reflect a reasonable capacity as possessed by humans. Rather, a system should be able instead to capture enough details to represent a common set of reasoning failures. I represent a number of examples with such a level of granularity and describe what such representations offer an intelligent system. This capacity will enable a system to reason about itself so as to learn from its reasoning failures, changing its background knowledge to avoid repetition of the failure. Two primitives are not sufficient for this task.
A Part-Based Skew Estimation Method

In this paper we propose a part-based skew estimation method which is more robust to larger varieties of text images, such as camera-captured scene images. Specifically, the skew angle at each local part of the input image is estimated independently by referring the local part of upright character images stored as a database. Then the global skew angle is estimated by aggregating the estimated local skews. The proposed method does not assume that characters are laid-out in straight lines and thus have more robustness to the varieties of text images than conventional methods. The experimental results show the advantage of the proposed method over the conventional methods under several conditions.
Analysis of the low-energy electron-recoil spectrum of the CDMS experiment

We report on the analysis of the low-energy electron-recoil spectrum from the CDMS II experiment using data with an exposure of 443.2 kg-days. The analysis provides details on the observed counting rate and possible background sources in the energy range of 2–8.5 keV. We find no significant excess of a peaked contribution to the total counting rate above the background model, and compare this observation to the recent DAMA results. In the framework of a conversion of a dark matter particle into electromagnetic energy, our 90% confidence level upper limit of 0.246 events/kg/day at 3.15 keV is lower than the total rate above background observed by DAMA. In absence of any specific particle physics model to provide the scaling in cross section between NaI and Ge, we assume a Z2 scaling. With this assumption the observed rate in DAMA remains higher than the upper limit in CDMS. Under the conservative assumption that the modulation amplitude is 6% of the total rate we obtain upper limits on the modulation amplitude a factor of ~2 lower than observed by DAMA, constraining some possible interpretations of this modulation.
Fast Surface Reconstruction from Contours using Implicit Surfaces

This paper presents a fast and efficient surface reconstruction method from contour data sets. The reconstructed surface is defined as an implicit surface. We create a stratification of the polygonal contours in each cross–section to speed–up the point membership classification involved in the field function computation and avoid the creation of a geometric skeleton. Tests carried out with medical scanner data–sets show that the reconstruction may be performed at interactive rates.
Development and Evaluation of Object-Based Visual Attention for Automatic Perception of Robots

Bottom-up visual attention is an automatic behavior to guide visual perception to a conspicuous object in a scene. This paper develops a new object-based bottom-up attention (OBA) model for robots. This model includes four modules: Extraction of preattentive features, preattentive segmentation, estimation of space-based saliency, and estimation of proto-object-based saliency. In terms of computation, preattentive segmentation serves as a bridge to connect the space-based saliency and object-based saliency. This paper therefore proposes a preattentive segmentation algorithm, which is able to self-determine the number of proto-objects, has low computational cost, and is robust in a variety of conditions such as noise and spatial transformations. Experimental results have shown that the propsoed OBA model outperforms space-based attention model and other object-based attention methods in terms of accuracy of attentional selection, consistency under a series of noise settings and object completion.
Modeling and experimental analysis of a Coupling Inductor employed in a high performance AC power source

A large number of papers regarding Coupling Inductors (CIs) for interleaved parallel connected converter stages is available in literature. However, to the knowledge of the authors, a comprehensive summary of the basics and a description of the modeling and the experimental analysis, as well as the conditions which must be satisfied to avoid saturation of the CI's core are still missing. This paper intends to close this gap partially based on research conducted on a multi-phase 3-level voltage source converter which is intended to be employed as a high performance AC power source. The main focus of the investigations is on CIs with high coupling factors k ≈ 1. Besides a detailed CI literature review, the focus is on the modeling of the component itself and on the analysis of the requirements for the targeted application. The separation of the coupling inductor currents and bridge-leg output voltages into longitudinal and transverse components is introduced to illustratively explain the CI's behavior. A complete investigation to avoid saturation in all operating conditions is conducted. Finally, the derived theoretical analysis and their conclusions are successfully verified by extensive measurements on a phase leg of a 10 kW 3-level voltage source converter prototype.
Biofuels Production through Biomass Pyrolysis —A Technological Review

There has been an enormous amount of research in recent years in the area of thermo-chemical conversion of biomass into bio-fuels (bio-oil, bio-char and bio-gas) through pyrolysis technology due to its several socio-economic advantages as well as the fact it is an efficient conversion method compared to other thermo-chemical conversion technologies. However, this technology is not yet fully developed with respect to its commercial applications. In this study, more than two hundred publications are reviewed, discussed and summarized, with the emphasis being placed on the current status of pyrolysis technology and its potential for commercial applications for bio-fuel production. Aspects of pyrolysis technology such as pyrolysis principles, biomass sources and characteristics, types of pyrolysis, pyrolysis reactor design, pyrolysis products and their characteristics and economics of bio-fuel production are presented. It is found from this study that conversion of biomass to bio-fuel has to overcome challenges such as understanding the trade-off between the size of the pyrolysis plant and feedstock, improvement of the reliability of pyrolysis reactors and processes to become viable for commercial applications. Further study is required to achieve a better understanding of the economics of biomass pyrolysis for bio-fuel production, as well as resolving issues related to the capabilities of this technology in practical application.
Capacity bounds for energy efficient data streaming in homogeneous wireless ad hoc networks

According to the Gaussian channel model, the throughput of a wireless link (u, v) is B log(l + S/N) bps, where B is the channel bandwidth and S/N is the signal to noise ratio. Wireless links which are scheduled simultaneously add to the noise levels of each other and cause the overall network capacity to decrease. In this paper we consider a wireless ad hoc network with unicast or multicast routing and simultaneously transmitting nodes along the route. Our major goal is to increase the capacity of the unicast/multicast sessions when all the wireless links are scheduled simultaneously. In addition, we try to minimize the number of active nodes involved in the unicast/multicast session for the purpose of energy efficiency. We assume that all the nodes share the same transmission range if activated and propose several node activation schemes with provable asymptotic bounds on the capacity and energy efficiency of the induced communication graph. We verify our results by simulations.