Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the felt sense of chronic ill-health: dialoguing between IPA, lifeworld theory and narrative inquiry to make sense of feelings and affect

ABSTRACT We present a pluralist approach to analysing emotion and affect within subjective lived experience. We illustrate this by re-engaging with data about living with Parkinson’s disease (PD) to more fully understand the felt sense of chronic ill health. Following Pierce, we engage in abductive reasoning to achieve this. The original data were generated using semi-structured interviews and analysed using interpretative phenomenological analysis. This inductive, idiographic analysis was our starting point. We then engaged in a dialogue between theory and data to further explicate the felt sense. Using the phenomenological theory of lifeworld revealed the presence and significance of emotion throughout and revealed the co-existence of well-being and suffering within the felt sense of PD. A narrative-oriented inquiry examined in detail the narrative structure within the retelling of the diagnosis and coming to terms with PD. Emotion was embedded in the account and revealed the prevailing mood within the experience.
The Smartphone is One of the Externalizations of the Mind that Aspires to the Status of its Extension

Is the Smartphone (SP) an extension of consciousness or just an (other) externalization of the mind and an extension of the social? The concept of externalizing the mind more appropriately describes a series of processes that tend to be considered extensions of the mind. The human mind has evolved concurrently with various externalizations, such as utensils and language, as contributions to the development of the common environment of humanity: culture and civilization. Externalizations indicate the appearance of the human mind while the extensions take into account the possibility of passing to another level (the singularity of consciousness). SP is a handy tool that mediates the personal relationship with the world, benefiting from a level of integration into the global workspace of the mind. Externalization called the SP could be a bridge from the externalization of the mind to its extensions, making the ontological leap from the utensil status to that of "part of the mind". SP is a mediator of an environment: it mediates between the mind and a special social environment called the Internet (mediates access to cognitive support provided by society through the virtual world), which is gradually becoming another reality.
Keck Spectroscopy of Redshift z ~ 3 Galaxies in the Hubble Deep Field

We have obtained spectra with the 10 m Keck telescope of a sample of 24 galaxies having colors consistent with star-forming galaxies at redshifts 2 ≲ z ≲ 4.5 in the Hubble deep field (HDF). Eleven of these galaxies are confirmed to be at high redshift (zmed = 3.0), one is at z = 0.5, and the other 12 have uncertain redshifts but have spectra consistent with their being at z > 2. The spectra of the confirmed high-redshift galaxies show a diversity of features, including weak Lyα emission, strong Lyα breaks or damped Lyα absorption profiles, and the stellar and interstellar rest-UV absorption lines common to local starburst galaxies and high-redshift star-forming galaxies reported recently by others. The narrow profiles and low equivalent widths of C IV, Si IV, and N V absorption lines may imply low stellar metallicities. Combined with the five high-redshift galaxies in the HDF previously confirmed with Keck spectra by Steidel et al. (1996a), the 16 confirmed sources yield a comoving volume density of n ≥ 2.4 × 10-4 h503 Mpc-3 for q0 = 0.05, or n ≥ 1.1 × 10-3 h503 Mpc-3 for q0 = 0.5. These densities are 3-4 times higher than the recent estimates of Steidel et al. (1996b) based on ground-based photometry with slightly brighter limits and are comparable to estimates of the local volume density of galaxies brighter than L*. The high-redshift density measurement is only a lower limit and could be almost 3 times higher still if all 29 of the unconfirmed candidates in our original sample, including those not observed, are indeed also at high redshift. The galaxies are small but luminous, with half-light radii 1.8 < r1/2 < 6.5 h50−1 kpc and absolute magnitudes -21.5 > MB > -23. The HST images show a wide range of morphologies, including several with very close, small knots of emission embedded in wispy extended structures. Using rest-frame UV continuum fluxes with no dust correction, we calculate star formation rates in the range 7-24 or 3-9 h50−2 M☉ yr-1 for q0 = 0.05 and q0 = 0.5, respectively. These rates overlap those for local spiral and H II galaxies today, although they could be more than twice as high if dust extinction in the UV is significant. If the objects at z = 3 were simply to fade by 5 mag (assuming a 107 yr burst and passive evolution) without mergers in the 14 Gyr between then and now (for q0 = 0.05, h50 = 1.0), they would resemble average dwarf elliptical/spheroidal galaxies in both luminosity and size. However, the variety of morphologies and the high number density of z = 3 galaxies in the HDF suggest that they represent a range of physical processes and stages of galaxy formation and evolution, rather than any one class of object, such as massive ellipticals. A key issue remains the measurement of masses. These high-redshift objects are likely to be the low-mass, starbursting building blocks of more massive galaxies seen today.
On a Difference-Delay Equation

Abstract We investigate how the behaviour, especially at ± ∞, of continuous real solutions f(t) to the equation f(t) = a1f(t + h1) + a2f(t − h2), where a1, a2, h1, h2 are positive real constants, depends on the values of these parameters. Definitive answers are given, except in certain cases when h1/h2 is rational.
There exist Boolean functions on n (odd) variables having nonlinearity > 2n-1 - 2(n-1)/2 if and only if n>7

For the first time we find Boolean functions on 9 variables having nonlinearity 241, that remained as an open question in literature for almost three decades. Such functions are discovered using a suitably modified steepest-descent based iterative heuristic search in the class of rotation symmetric Boolean functions (RSBFs). This shows that there exist Boolean functions on n (odd) variables having nonlinearity > 2n−1 − 2 n−1 2 if and only if n > 7. Using the same search method, we also find several other important functions and we study the autocorrelation, propagation characteristics and resiliency of the RSBFs (using proper affine transformations, if required). The results show that it is possible to get balanced Boolean functions on n = 10 variables having autocorrelation spectra with maximum absolute value < 2 n 2 , which was not known earlier. In certain cases the functions can be affinely transformed to get first order propagation characteristics. We also obtain 10-variable functions having first order resiliency and nonlinearity 492 which was posed as an open question in Crypto 2000.
SPARSITY-AIDED RADAR WAVEFORM SYNTHESIS

Owing to the inherent sparsity of the target scene, compressed sensing (CS) has been successfully employed in radar applications. It is known that the performance of target scene recovery in CS scenarios depends highly on the coherence of the sensing matrix (CSM), which is determined by the radar transmit waveform. In this paper, we present a cyclic optimization algorithm to effectively reduce the CSM via a judicious design of the radar waveform. The proposed method provides a reduction in the size of the Gram matrix associated with the sensing matrix, and moreover, relies on the fast Fourier transform (FFT) operations to improve the computation speed. As a result, the suggested algorithm can be used for large dimension designs (with & 100 variables) even on an ordinary PC. The effectiveness of the proposed algorithm is illustrated through numerical examples.
Self-Organizing Map-based Applications in Remote Sensing

Remote sensing involves the collection of information about an object from a distance. Often remote-sensing instruments are mounted onboard an airor space-borne platform and typically record electromagnetic energy in specific wavelength intervals, or bands. The electromagnetic energy recorded over a given area contains information about surfaces reflecting or emitting energy. This information can be used for a variety of applications; for example, remote-sensing image analysis can extract thematic information such as land-cover types (Jensen, 2005). Artificial neural network (ANN) techniques have increasingly been employed in the analysis of remotely-sensed images. ANNs can be advantageous in digital image processing in that no assumption is made about the statistical properties of the images, and they are thus widely applicable to a variety of dataset types. In addition, ANNs learn adaptively through examples and have a high tolerance to noisy or incomplete data (Jensen, 2005). ANN model development can proceed via either supervised or unsupervised means, and if adequate training data are available, supervised training may be readily performed. However, obtaining reliable training data in remote-sensing applications is often problematic (Congalton and Green, 1999), as a remote sensor image typically covers a large area, and only a limited number of training locations can be sampled in the field due to cost, time, personnel requirements, and various other logistical constraints, including potential restrictions on access to the study area. Unsupervised image-processing methods— including unsupervised ANNs—can be of significant utility in such circumstances (Filippi et al., 2009). Unsupervised ANNs are used in situations where the correct outputs may not be known, or if it is desired that the network discover or categorize regularities or features in the training data on its own. There is no teacher signal (Hassoun, 1995). The unsupervised Kohonen self-organizing map (SOM) is a two-layer network, with an input fan-out layer, and an output layer (known as the Kohonen or competitive layer), and the method is based upon competitive learning. The Kohonen layer is comprised of a physical net of neurons located at fixed positions (i.e., intersections in a grid of square meshes). Adjacent neurons are assumed to have a Euclidean distance of unity. The input 14
Private and Efficient Stable Marriages (Matching)

We provide algorithms guaranteeing high levels of privacy by computing uniformly random solutions to stable marriages problems. We also provide efficient algorithms extracting a nonuniformly random solution and guaranteeing t-privacy for any threshold t. The most private solution is expensive and is based on a distributed/shared CSP model of the problem. The most efficient version is based on running the Gale-Shapley algorithm after shuffling the men (or women) in the shared secret description of the problem. We introduce an efficient arithmetic circuit for the Gale-Shapley algorithm that can employ a cryptographic primitive we propose for vector access with an arbitrary number of participants. Participants want to find a stable matching as defined by their secret preferences and without leaking any of these secrets. An additional advantage of the solvers based on secure simulations of arithmetic circuits is that it returns a solution picked randomly among existing solutions. Besides the fact that this increases privacy to a level of requested t-privacy, it also provides fairness to participants. A real implementation of a described secure solution usable by participants on distinct computers on the Internet is implemented (by students in a class assignment) and is available on our web-site.
Lost in the crowd: Conformity as escape following disbelief in free will

Belief in free will is founded on the idea that people are responsible for their behavior. People who believe in free will derive meaning in life from these beliefs. Conformity refers to succumbing to external pressures and imitating others’ behaviors. Sometimes, conformity involves a loss of self-awareness, which reduces perceived meaninglessness. We tested if disbelief in free will increases perceived meaninglessness and if people subsequently become more conformist to address this negative existential perception. We conducted three studies to test this hypothesis. In Study 1, experimentally induced disbelief in free will resulted in perceived meaninglessness. In Study 2, perceived meaninglessness correlated with conformity. Finally, in Study 3, perceived meaninglessness mediated the relationship between disbelief in free will and conformity, especially under high self-awareness. We conclude that perceptions about meaning play a central role in the relationship between disbelief in free will and conformity.
Peripheral Nerve Regeneration A Novel Use of Genipin-Fixed Gelatin as Extracellular Matrix for

Application of combining herbal medicine and biomedical material science to nerve regeneration is a new approach. In this study, we describe a novel use of purified genipin, which can be extracted from Gardenia jasminoides Ellis, fixing the gelatin to be an extracellular matrix for peripheral nerve regeneration. A 10-mm gap of rat sciatic nerve was created between the proximal and distal nerve stumps, which were sutured into silicone rubber tubes filled with either the genipin-fixed gelatin or collagen gel. Silicone rubber tubes filled with saline were used as controls. Six weeks after implantation, regeneration across the nerve gaps occurred in 80 and 90% of the animals from *Author to whom correspondence should be addressed. E-mail: yuehsc@mail.cmu. edu.tw JOURNAL OF BIOMATERIALS APPLICATIONS Volume 19 — July 2004 21 0885-3282/04/01 0021–14 $10.00/0 DOI: 10.1177/0885328204042544 2004 Sage Publications + [Ver: 7.51g/W] [11.6. 2004–7:43am] [21–34] [Page No. 21] FIRST PROOFS I:/Sage/Jba/Jba19-1/JBA-42544.3d (JBA) Paper: JBA-42544 Keyword © 2004 SAGE Publications. All rights reserved. Not for commercial use or unauthorized distribution. at PENNSYLVANIA STATE UNIV on April 10, 2008 http://jba.sagepub. com Downloaded from the groups of genipin-fixed gelatin and collagen, respectively, whereas only 30% in the control group. Large numbers of myelinated axons were also seen in the genipin-fixed gelatin (5104 3278) and the collagen groups (8063 1807). These findings indicated that the genipin-fixed gelatin could be an acceptable extracellular matrix for nerve regeneration.
Sinusoidal + all-pole modification based spectral smoothing for concatenative speech synthesis

The conventional LPC spectral smoothing algorithm causes an evident degradation in the speech quality when the smoothing amount is large. To improve speech quality of the smoothed speech, we proposed a new spectral smoothing algorithm. The source LPC spectral envelopes are first interpolated to generate the smoothed target spectra. Then the sinusoidal + all-pole modification is performed on the source speech to get the spectra of the modified speech which will coincide with the target spectra. Experimental results show that this method can get smooth spectral envelope even if the speech boundaries have large spectral distance. Experimental results prove that this algorithm is effective on avoiding degradation in quality of smoothed speech.
Methodology Support for the Model Driven Architecture

Model-driven approaches to software engineering have expanded their influence in recent years, with Object Management Group's model-driven architecture (MDA) being the major force behind this boost. However, despite its merits, MDA remains insufficient for software system development, in the sense that it does not provide a concrete and comprehensive process for governing software development activities. There is therefore a strongly felt need for new model-driven software development methodologies. In this paper we review a number of existing model-driven methodologies, and propose a general framework for model-driven development (MDD) based on MDA. The framework can be used for assessing and comparing methodologies, engineering new methodologies, and adapting existing ones so that they meet the special requirements of the model-driven approach. We have used the framework herein to show how agile methodologies fare in this model-driven development context.
Evaluation of Serum Cystatin C as a Marker of Early Renal Impairment in Patients with Liver Cirrhosis

Background. Serum cystatin C (CysC) was proposed as an effective reflection of the glomerular filtration rate (GFR). However, its role in patients with liver cirrhosis has not been extensively verified especially in the detection of early RI. Patients and Methods. Seventy consecutive potential candidates for living donor liver transplantation with serum creatinine (Cr) <1.5 mg/dL were included. CysC, Cr, and estimated GFR [creatinine clearance (CCr), Cockcroft-Gault formula (C-G), MDRD equations with 4 and 6 variables, CKD-EPI-Cr, CKD-EPI-CysC, and CKD-EPI-Cr-CysC] were all correlated to isotopic GFR. Early RI was defined as GFR of 60–89 mL/min/1.73 m2. Results. Patients were 25.7% and 74.3% Child-Pugh classes B and C, respectively. GFR was ≥90, 60–89, and 30–59 mL/min/1.73 m2 in 31.4%, 64.3%, and 4.3% of the patients, respectively. All markers and equations, except C-G, were significantly correlated to GFR with CKD-EPI-Cr-CysC formula having the highest correlation (r = 0.474) and the largest area under the ROC curve (0.808) for discriminating early RI. At a cutoff value of 1.2 mg/L, CysC was 89.6% sensitive and 63.6% specific in detecting early RI. Conclusion. In patients with liver cirrhosis, CysC and CysC-based equations showed the highest significant correlation to GFR and were measures that best discriminated early RI.
A GENERAL MULTIVARIATE EXTENSION OF FISHER'S GEOMETRICAL MODEL AND THE DISTRIBUTION OF MUTATION FITNESS EFFECTS ACROSS SPECIES

Abstract The evolution of complex organisms is a puzzle for evolutionary theory because beneficial mutations should be less frequent in complex organisms, an effect termed “cost of complexity. ” However, little is known about how the distribution of mutation fitness effects (f(s)) varies across genomes. The main theoretical framework to address this issue is Fisher's geometric model and related phenotypic landscape models. However, it suffers from several restrictive assumptions. In this paper, we intend to show how several of these limitations may be overcome. We then propose a model of f(s) that extends Fisher's model to account for arbitrary mutational and selective interactions among n traits. We show that these interactions result in f(s) that would be predicted by a much smaller number of independent traits. We test our predictions by comparing empirical f(s) across species of various gene numbers as a surrogate to complexity. This survey reveals, as predicted, that mutations tend to be more deleterious, less variable, and less skewed in higher organisms. However, only limited difference in the shape of f(s) is observed from Escherichia coli to nematodes or fruit flies, a pattern consistent with a model of random phenotypic interactions across many traits. Overall, these results suggest that there may be a cost to phenotypic complexity although much weaker than previously suggested by earlier theoretical works. More generally, the model seems to qualitatively capture and possibly explain the variation of f(s) from lower to higher organisms, which opens a large array of potential applications in evolutionary genetics.
Kernel Bayes' rule: Bayesian inference with positive definite kernels

A kernel method for realizing Bayes' rule is proposed, based on representations of probabilities in reproducing kernel Hilbert spaces. Probabilities are uniquely characterized by the mean of the canonical map to the RKHS. The prior and conditional probabilities are expressed in terms of RKHS functions of an empirical sample: no explicit parametric model is needed for these quantities. The posterior is likewise an RKHS mean of a weighted sample. The estimator for the expectation of a function of the posterior is derived, and rates of consistency are shown. Some representative applications of the kernel Bayes' rule are presented, including Bayesian computation without likelihood and filtering with a nonparametric state-space model.
Origins of ... image analysis in clinical pathology.

The term "image analysis" is reserved for a special discipline in pathology that aims to obtain diagnostically important information in an objective and reproducible manner, by measuring and counting. The origins of measuring microscopical images are almost as old as the microscope itself. Leeuwenhoek (fig 1) in the 17th century had developed a system to measure microscopic objects. As a reference he used sand grains of different sizes, and hairs from his head, beard or wig. ' 2 Using this method, in 1674 he measured human erythrocytes as 25 000 times smaller than a small sand grain, corresponding to 8.5 gm.3 Given the means at his disposal, this is amazingly precise. This review intends to give an overview of the developments that have led to image analysis as it is currently applied in routine diagnostic cytopathology and histopathology as well as in research. For the purpose of clarity we discriminate between three different areas of image analysis; however, they are not mutually exclusive. These areas are measuring morphological characteristics of tissues, cells, nuclei or even nucleoli; counting of cell or tissue components; and cytometry and pattern recognition, which aims to measure cytochemical, histochemical, and molecular cell or tissue features
Maximum-Utility Scheduling of Operation Modes With Probabilistic Task Execution Times Under Energy Constraints

We propose a novel scheduling scheme that determines the instant operation modes of multiple tasks. The tasks have probabilistic execution times and are executed on discrete operation modes providing different utilities with different energy consumptions. We first design an optimal offline scheduling scheme that stochastically maximizes the cumulative utility of the tasks under energy constraints, at the cost of heavy computational overhead. Next, the optimal offline scheme is modified to an approximate online scheduling scheme. The online scheme has little runtime overhead and yields almost the maximum utility, with an energy budget that is given at runtime. The difference between the maximum utility and the output utility of the online scheme is bounded by a controllable input value. Extensive evaluation shows that the output utility of the online scheme approaches the maximum utility in most cases, and is much higher than that of existing methods by up to 50% of the largest utility difference among available operation modes.