Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in corneal wavefront aberrations with aging.

PURPOSE To investigate whether corneal wavefront aberrations vary with aging. METHODS One hundred two eyes of 102 normal subjects were evaluated with videokeratography. The data were decomposed using Taylor and Zernike polynomials to calculate the monochromatic aberrations of the cornea for both small (3-mm) and large (7-mm) pupils. RESULTS For a 3-mm pupil, the amount of total aberrations (Spearman rank correlation coefficient r(s) = 0.145; P = 0.103) and spherical-like aberrations (r(s) = -0.068; P = 0.448) did not change with aging, whereas comalike aberrations exhibited a weak but statistically significant correlation with age (r(s) = 0.256; P = 0.004). For a 7-mm pupil, total aberrations (r(s) = 0.552; P < 0.001) and comalike aberrations (r(s) = 0.561; P < 0.001) significantly increased with aging, but spherical-like aberrations showed no age-related changes (r(s) = 0.124; P = 0.166). Simulated pupillary dilation from 3 mm to 7 mm caused a 38.0+/-28.5-fold increase in the total aberrations, and the extent of increases significantly correlated with age (r(s) = 0.354; P < 0.001). Pupillary dilation influenced the comalike aberrations more in the older subjects than in the younger subjects (r(s) = 0.243; P = 0.006), but such age dependence was not found for spherical-like aberrations (r(s) = 0.141; P = 0.115). CONCLUSIONS Comalike aberrations of the cornea correlate with age, implying that the corneas become less symmetrical along with aging. Spherical-like aberrations do not vary significantly with aging. Pupillary dilation markedly increases wavefront aberrations, and those effects are more prominent in older subjects than in younger subjects.
Suboptimal initiation of dialysis with and without early referral to a nephrologist.

BACKGROUND Our objective was to examine patients who initiate renal replacement therapy (RRT) at 10 representative Canadian centers, characterize their initiation as inpatient or outpatient and describe their initial type of dialysis access, duration of pre-dialysis care and clinical status at the time of dialysis initiation. We also examined the impact of an optimal dialysis start (i.e. initiated as an outpatient with an arteriovenous fistula, arteriovenous graft or peritoneal dialysis catheter) on subsequent health outcomes. METHODS Charts of consecutive incident RRT patients were identified from 1 July to 31 December 2006. Information was collected until 6 months after the initiation or until death, transplant or transfer. RESULTS Three hundred and thirty-nine incident RRT patients were studied: 39.6% initiated as an inpatient; 54% started hemodialysis (HD) with a central venous catheter; 15.3% had <1 month predialysis care, while 64.6% had >1 year. Optimal starts occurred in 39.5% of patients. For HD patients, optimal starts occurred in 19.8%. Suboptimal starts were noted in patients referred <12 months prior to end-stage renal disease (44%) and in patients referred earlier (56%). The composite end point of death, transfusion or subsequent hospitalization was significantly reduced with an optimal start [hazard ratio 0.47 (95% confidence interval 0.32-0.68), P = 0.0001]. CONCLUSIONS Suboptimal initiation of dialysis is common in patients referred early or late. The benefits of early referral are lost if dialysis is initiated suboptimally. There is a need to identify factors that lead to suboptimal initiation despite early referral.
Spectrally optimal sampling for distribution ray tracing

Nonuniform sampling of images is a useful technique in computer graphics, because a properly designed pattern of samples can make aliasing take the form of high-frequency random noise. In this paper, the technique of nonuniform sampling is extended from two dimensions to include the extra parameter dimensions of distribution ray tracing. A condition for optimality is suggested, and algorithms for approximating optimal sampling are developed. The technique is demonstrated at low sampling densities, so the characteristics of aliasing noise are clearly visible. At supersampling rates, this technique should move noise into frequencies above the passband of the pixel-reconstruction filter.
RED NUGGETS AT z ∼ 1.5: COMPACT PASSIVE GALAXIES AND THE FORMATION OF THE KORMENDY RELATION

We present the results of Near-Infrared Camera and Multi-Object Spectrometer (NICMOS) imaging of a sample of 19 high-mass passively evolving galaxies with 1.2 < z < 2, taken primarily from the Gemini Deep Deep Survey (GDDS). Around 80% of galaxies in our GDDS sample have spectra dominated by stars with ages ≳1 Gyr. Our rest-frame R-band images show that most of these objects have compact regular morphologies which follow the classical R1/4 law. These galaxies scatter along a tight sequence in the size versus surface brightness parameter space which defines the Kormendy relation. Around one-third (3/10) of the massive red objects in the GDDS sample are extraordinarily compact, with effective radii under 1 kpc. Our NICMOS observations allow the detection of such systems more robustly than is possible with optical (rest-frame UV) data, and while similar systems have been seen at z ≳ 2, this is the first time such systems have been detected in a rest-frame optical survey at 1.2 < z < 2. We refer to these compact galaxies as “red nuggets,” and note that similarly compact massive galaxies are completely absent in the nearby universe. We introduce a new “stellar mass Kormendy relation” (stellar mass density versus size) which we use to single out the effects of size evolution from those of luminosity and color evolution in stellar populations. The 1 < z < 2 passive galaxies have mass densities that are an order of magnitude larger then early-type galaxies today and are comparable to the compact distant red galaxies at 2 < z < 3. We briefly consider mechanisms for size evolution in contemporary models focusing on equal-mass mergers and adiabatic expansion driven by stellar mass loss. Neither of these mechanisms appears to be able to transform the high-redshift Kormendy relation into its local counterpart, leaving the origin and fate of these compact “red nuggets” unresolved.
k‐t BLAST reconstruction from non‐Cartesian k‐t space sampling

Current implementations of k‐t Broad‐use Linear Acqusition Speed‐up Technique (BLAST) require the sampling in k‐t space to conform to a lattice. To permit the use of k‐t BLAST with non‐Cartesian sampling, an iterative reconstruction approach is proposed in this work. This method, which is based on the conjugate gradient (CG) method and gridding reconstruction principles, can efficiently handle data that are sampled along non‐Cartesian trajectories in k‐t space. The approach is demonstrated on prospectively gated radial and retrospectively gated Cartesian imaging. Compared to a sliding window (SW) reconstruction, the resulting image series exhibit lower artifact levels and improved temporal fidelity. The proposed approach thus allows investigators to combine the specific advantages of non‐Cartesian imaging or retrospective gating with the acceleration provided by k‐t BLAST. Magn Reson Med, 2006. © 2005 Wiley‐Liss, Inc.
Wavelet statistical models and Besov spaces

We discover a new relationship between two seemingly different image modeling methodologies; the Besov space theory and the wavelet-domain statistical image models. Besov spaces characterize the set of real-world images through a deterministic characterization of the image smoothness, while statistical image models capture the probabilistic properties of images. By establishing a relationship between the Besov norm and the normalized likelihood function under an independent wavelet-domain generalized Gaussian model, we obtain a new interpretation of the Besov norm which provides a natural generalization of the theory for practical image processing. Base don this new interpretation of the Besov space, we propose a new image denoising algorithm based on projections onto the convex sets defined in the Besov space. After pointing out the limitations of Besov space, we propose possible generalizations using more accurate image models.
Do Insider Trading Laws Work?

By calculating an estimated measure of undetected insider trading, this paper shows that profits made by informed corporate insiders prior to tender offer announcements increase after the first enforcement of insider trading laws. I analyze the effects of Insider Trading regulation on a sample of 5,099 acquisitions in 56 different countries, and estimate the profits due to insider trading from the abnormal volume in the weeks prior to the announcement, under the assumption that insiders purchase those shares at the prevailing price and hold them until the public announcement. I find that laws that prosecute insider trading fail to eliminate profits made by insiders, and make acquisitions more expensive. Therefore, by increasing the market reaction to an acquisition, insider trading laws make it profitable to violate them.
Quantum-gravity and minimum length

The existence of a fundamental scale, a lower bound to any output of a position measurement, seems to be a model-independent feature of quantum gravity. In fact, different approaches to this theory lead to this result. The key ingredients for the appearance of this minimum length are quantum mechanics, special relativity and general relativity. As a consequence, classical notions such as causality or distance between events cannot be expected to be applicable at this scale. They must be replaced by some other, yet unknown, structure.
Towards cosmological concordance on galactic scales

We use the observed abundance and clustering of galaxies from the 2dF Galaxy Redshift Survey to determine the matter density Ω m and the linear amplitude of mass fluctuations σ 8 . We use a method based on the conditionalluminosity function, which allows straightforward computation of the luminosity-dependent bias, b, of galaxies with respect to the matter distribution. This allows us to break the degeneracy between bias and σ 8 , which has hampered previous attempts of using large-scale structure (LSS) data to determine σ 8 . In addition, it allows the inclusion of constraints on the redshift space distortion parameter β = Ω 0 . 6 m/b, and yields average mass-to-light ratios as a function of halo mass. Using only the luminosity function and the correlation lengths as a function of luminosity we obtain constraints on Ω m and σ 8 that are in good agreement with COBE. Models with low Ω m and high σ 8 as well as those with high Ω m and low σ 8 are ruled out because they over (under)predict the amount of clustering, respectively. We find the cluster mass-to-light ratio, (M v i r /L) c 1 , to be strongly correlated with σ 8 . Using the additional constraints (M v i r /L) c l = (350 ′ 70) h (M/L) O . and β = 0.49 ′ 0.09 as Gaussian priors significantly tightens the constraints and allows us to break the degeneracy between Ω m and σ 8 . For flat A-cold dark matter (ACDM) cosmologies with scale-invariant power spectra, we obtain that Ω m = 0.27 + 0 . 1 4 -0.10 and σ 8 = 0.70 ′ 0.11 (both 95 per cent confidence limit). Adding constraints from current cosmic microwave background data, and extending the analysis to a larger cosmological parameter space, we obtain that Ω m = 0.24 ′ 0.07 and σ 8 = 0.74 + 0 . 1 3 -0.10 (both 95 per cent confidence limit). Thus, we find clear evidence that both the matter density Ω m and the mass variance σ 8 are significantly lower than their 'standard' concordance values of 0.3 and 0.9, respectively. We show that cosmologies with Ω m ≃ 0.25 and a 8 ≃ 0.75, as favoured here, predict dark matter haloes that are significantly less centrally concentrated than for the standard ACDM concordance cosmology. We argue that this may solve both the problem with the rotation curves of dwarf and low surface brightness galaxies, as well as the problem of simultaneously matching the galaxy luminosity function and the Tully-Fisher zero-point.
PAC-Bayesian Analysis of Co-clustering and Beyond

We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models, graph clustering, and pairwise clustering. We begin with the analysis of co-clustering, which is a widely used approach to the analysis of data matrices. We distinguish among two tasks in matrix data analysis: discriminative prediction of the missing entries in data matrices and estimation of the joint probability distribution of row and column variables in co-occurrence matrices. We derive PAC-Bayesian generalization bounds for the expected out-of-sample performance of co-clustering-based solutions for these two tasks. The analysis yields regularization terms that were absent in the previous formulations of co-clustering. The bounds suggest that the expected performance of co-clustering is governed by a trade-off between its empirical performance and the mutual information preserved by the cluster variables on row and column IDs. We derive an iterative projection algorithm for finding a local optimum of this trade-off for discriminative prediction tasks. This algorithm achieved state-of-the-art performance in the MovieLens collaborative filtering task. Our co-clustering model can also be seen as matrix tri-factorization and the results provide generalization bounds, regularization terms, and new algorithms for this form of matrix factorization. The analysis of co-clustering is extended to tree-shaped graphical models, which can be used to analyze high dimensional tensors. According to the bounds, the generalization abilities of tree-shaped graphical models depend on a trade-off between their empirical data fit and the mutual information that is propagated up the tree levels. We also formulate weighted graph clustering as a prediction problem: given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. The analysis of co-clustering easily extends to this problem and suggests that graph clustering should optimize the trade-off between empirical data fit and the mutual information that clusters preserve on graph nodes.
A capability­based view of organisational renewal: combining opportunity­ and advantage­seeking growth in large, established European and North American wood­industry companies

The purpose of this study was to extend understanding of how large firms pursuing sustained and profitable growth manage organisational renewal. A multiple-case study was conducted in 27 North American and European wood-industry companies, of which 11 were chosen for closer study. The study combined the organisational-capabilities approach to strategic management with corporate-entrepreneurship thinking. It charted the further development of an identification and classification system for capabilities comprising three dimensions: (i) the dynamism between firm-specific and industry-significant capabilities, (ii) hierarchies of capabilities and capability portfolios, and (iii) their internal structure. Capability building was analysed in the context of the organisational design, the technological systems and the type of resource-bundling process (creating new vs. entrenching existing capabilities). The thesis describes the current capability portfolios and the organisational changes in the case companies. It also clarifies the mechanisms through which companies can influence the balance between knowledge search and the efficiency of knowledge transfer and integration in their daily business activities, and consequently the diversity of their capability portfolio and the breadth and novelty of their product/service range. The largest wood-industry companies of today must develop a seemingly dual strategic focus: they have to combine leading-edge, innovative solutions with cost-efficient, largescale production. The use of modern technology in production was no longer a primary source of competitiveness in the case companies, but rather belonged to the portfolio of basic capabilities. Knowledge and information management had become an industry imperative, on a par with cost effectiveness. Yet, during the period of this research, the case companies were better in supporting growth in volume of the existing activity than growth through new economic activities. Customer-driven, incremental innovation was preferred over firm-driven innovation through experimentation. The three main constraints on organisational renewal were the lack of slack resources, the aim for lean, centralised designs, and the inward-bound communication climate.
The Millennium Galaxy Catalogue: the B-band attenuation of bulge and disc light and the implied cosmic dust and stellar mass densities

Based on our sample of 10 095 galaxies with bulge‐disc decompositions we derive the empirical BMGC-band internal attenuation‐inclination relation for galaxy discs and their associated central bulges. Our results agree well with the independently derived dust models of Tuffs et al., leading to a direct constraint on the mean opacity of spiral discs of τ f = 3.8 ± 0.7 (central face-on BMGC-band opacity). Depending on inclination, the BMGC-band attenuation correction varies from 0.2 to 1.1 mag for discs and from 0.8 to 2.6 mag for bulges. We find that, overall, 37 per cent of all BMGC-band photons produced in discs in the nearby Universe are absorbed by dust, a figure that rises to 71 per cent for bulge photons. The severity of internal dust extinction is such that one must incorporate internal dust corrections in all optical studies of large galaxy samples. This is particularly pertinent for optical Hubble Space Telescope comparative evolutionary studies as the dust properties will also be evolving. We use the new results to revise our recent estimates of the spheroid and disc luminosity functions. The implied stellar mass densities at redshift zero are somewhat higher than our earlier estimates: ρdiscs =
IMP1, an mRNA binding protein that reduces the metastatic potential of breast cancer in a mouse model

Cells that are able to localize β-actin mRNA efficiently have decreased metastatic potential. Invasive carcinoma cells derived from primary mammary tumors have reduced levels of an RNA binding protein IMP1/ZBP1/IGF2BP1, required for β-actin mRNA localization. We showed previously that in human breast carcinoma cells in vitro, this protein suppresses invasion. In this work we examined whether its re-expression can suppress breast cancer metastasis in a breast cancer mouse model. We developed a mouse conditionally expressing IMP1-GFP (hereinafter referred to as the IMP1 transgene) specifically in the mammary gland of a PYMT breast cancer mouse. We found that mice conditionally expressing the IMP1 transgene showed little or no metastases to the lungs from the primary tumor in contrast to PYMT mice not expressing IMP1, which uniformly develop metastases at an early stage.
Alcoa: the Alloy constraint analyzer

Alcoa is a tool for analyzing object models. It has a range of uses. At one end, it can act as a support tool for object model diagrams, checking for consistency of multiplicities and generating sample snapshots. At the other end, it embodies a lightweight formal method in which subtle properties of behaviour can be investigated. Alcoa's input language, Alloy, is a new notation based on Z. Its development was motivated by the need for a notation that is more closely tailored to object models (in the style of UML), and more amenable to automatic analysis. Like Z, Alloy supports the description of systems whose state involves complex relational structure. State and behavioural properties are described declaratively, by conjoining constraints. This makes it possible to develop and analyze a model incrementally, with Alcoa investigating the consequences of whatever constraints are given. Alcoa works by translating constraints to boolean formulas, and then applying state-of-the-art SAT solvers. It can analyze billions of states in seconds.
Modelling the Ecological Comorbidity of Acute Respiratory Infection, Diarrhoea and Stunting among Children Under the Age of 5 Years in Somalia

The aim of this study was to assess spatial co‐occurrence of acute respiratory infections (ARI), diarrhoea and stunting among children of the age between 6 and 59 months in Somalia. Data were obtained from routine biannual nutrition surveys conducted by the Food and Agriculture Organization 2007–2010. A Bayesian hierarchical geostatistical shared component model was fitted to the residual spatial components of the three health conditions. Risk maps of the common spatial effects at 1×1 km resolution were derived. The empirical correlations of the enumeration area proportion were 0.37, 0.63 and 0.66 for ARI and stunting, diarrhoea and stunting and ARI and diarrhoea, respectively. Spatially, the posterior residual effects ranged 0.03–20.98, 0.16–6.37 and 0.08–9.66 for shared component between ARI and stunting, diarrhoea and stunting and ARI and diarrhoea, respectively. The analysis showed clearly that the spatial shared component between ARI, diarrhoea and stunting was higher in the southern part of the country. Interventions aimed at controlling and mitigating the adverse effects of these three childhood health conditions should focus on their common putative risk factors, particularly in the South in Somalia.
Wheelchair Basketball Skills Proficiencies versus Disability Classification

An investigation was undertaken to assess the relationship between the disability classification levels of wheelchair basketball players, as used by the National Wheelchair Basketball Association (NWBA), and the skill proficiency levels of the athlete. The assessment tool consisted of seven components deemed necessary for proficiency in basketball; these items were the 20-m sprint, free-throw shooting, obstacle dribble, baskets per minute, rebounding, speed pass, and pass for accuracy. The data used for statistical analysis were based upon the results acquired from 91 subjects who were tested in 1983. These subjects represented 18 NWBA teams from 14 states and Canada. The results of the investigation indicate support for placing less of an emphasis on the disability levels of wheelchair basketball participants, and for the development of functional assessment tools to be used in judging performances of “handicapped” athletes.
cis-Element- and Transcriptome-Based Screening of Root Hair-Specific Genes and Their Functional Characterization in Arabidopsis1[C][W][OA]

Understanding the cellular differentiation of multicellular organisms requires the characterization of genes whose expression is modulated in a cell type-specific manner. The Arabidopsis (Arabidopsis thaliana) root hair cell is one model for studying cellular differentiation. In this study, root hair cell-specific genes were screened by a series of in silico and experimental filtration procedures. This process included genome-wide screening for genes with a root hair-specific cis-element in their promoters, filtering root-specific genes from the root hair-specific cis-element-containing genes, further filtering of genes that were suppressed in root hair-defective plant lines, and experimental confirmation by promoter assay. These procedures revealed 19 root hair-specific genes, including many protein kinases and cell wall-related genes, most of which have not been characterized thus far. Functional analyses of these root hair-specific genes with loss-of-function mutants and overexpressing transformants revealed that they play roles in hair growth and morphogenesis. This study demonstrates that a defined cis-element can serve as a filter to screen certain cell type-specific genes and implicates many new root hair-specific genes in root hair development.