Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality of life in young‐ compared with late‐onset Parkinson's disease

The impact of Parkinson's disease on quality of life may vary depending on age at onset. We investigated the effect of age at onset on quality of life in a large Parkinson's disease population (n = 426) using a disease‐specific rating scale (PDQ‐39) and with careful adjustment for confounding and intermediary factors. We also explored the relationship between depression and excessive daytime sleepiness by age at onset and compared this with the general population. We found that a younger age at onset was significantly associated with worse overall quality of life scores (odds ratio, 2.66; 95% confidence interval, 1.39–5.09; P = .003), but this was attenuated by adjustment for depression as an intermediary factor (odds ratio, 1.86; 95% confidence interval, 0.84–4.11; P = .13). Younger onset was also a risk factor for poor emotional well‐being independent of depression status. Risk of depression and excessive daytime sleepiness were elevated in patients with Parkinson's disease compared with controls (odds ratio, 2.99; 95% confidence interval, 1.93–4.65; P < .001; and odds ratio, 3.84; 95% confidence interval, 2.56–5.75; P < .001, respectively), with similar findings seen in both early‐ and late‐onset groups. Our study highlights the need for accurate diagnosis and treatment of depression in younger‐onset patients in order to improve quality of life. © 2011 Movement Disorder Society
On the degrees-of-freedom of the 3-user MISO broadcast channel with hybrid CSIT

The 3-user multiple-input single-output (MISO) broadcast channel (BC) with hybrid channel state information at the transmitter (CSIT) is considered. In this framework, there is perfect and instantaneous CSIT from a subset of users and delayed CSIT from the remaining users. We present new results on the sum degrees of freedom (DoF) of the 3-user MISO BC with hybrid CSIT. In particular, for the case of 2 transmit antennas, we show that with perfect CSIT from one user and delayed CSIT from the remaining two users, the optimal sum DoF is 5/3. For the case of 3 transmit antennas and the same hybrid CSIT setting, it is shown that a higher sum DoF of 9/5 is achievable and this result improves upon the best known bound. Furthermore, with 3 transmit antennas, and the hybrid CSIT setting in which there is perfect CSIT from two users and delayed CSIT from the third one, a novel scheme is presented which achieves 9/4 sum DoF. Our results also reveal new insights on how to utilize hybrid channel knowledge for multi-user scenarios.
Coordinated induction of multi-gene pathways in Saccharomyces cerevisiae

Bacterial operons are nature’s tool for regulating and coordinating multi-gene expression in prokaryotes. They are also a gene architecture commonly used in the biosynthesis of many pharmaceutically important compounds and industrially useful chemicals. Despite being an important eukaryotic production host, Saccharomyces cerevisiae has never had such gene architecture. Here, we report the development of a system to assemble and regulate a multi-gene pathway in S. cerevisiae. Full pathways can be constructed using pre-made parts from a plasmid toolbox. Subsequently, through the use of a yeast strain containing a stably integrated gene switch, the assembled pathway can be regulated using a readily available and inexpensive compound—estradiol—with extremely high sensitivity (10 nM). To demonstrate the use of the system, we assembled the five-gene zeaxanthin biosynthetic pathway in a single step and showed the ligand-dependent coordinated expression of all five genes as well as the tightly regulated production of zeaxanthin. Compared with a previously reported constitutive zeaxanthin pathway, our inducible pathway was shown to have 50-fold higher production level.
Wettability impact on supercritical CO2 capillary trapping: Pore‐scale visualization and quantification

How the wettability of pore surfaces affects supercritical (sc) CO2 capillary trapping in geologic carbon sequestration (GCS) is not well understood, and available evidence appears inconsistent. Using a high‐pressure micromodel‐microscopy system with image analysis, we studied the impact of wettability on scCO2 capillary trapping during short‐term brine flooding (80 s, 8–667 pore volumes). Experiments on brine displacing scCO2 were conducted at 8.5 MPa and 45°C in water‐wet (static contact angle θ = 20° ± 8°) and intermediate‐wet (θ = 94° ± 13°) homogeneous micromodels under four different flow rates (capillary number Ca ranging from 9 × 10−6 to 8 × 10−4) with a total of eight conditions (four replicates for each). Brine invasion processes were recorded and statistical analysis was performed for over 2000 images of scCO2 saturations, and scCO2 cluster characteristics. The trapped scCO2 saturation under intermediate‐wet conditions is 15% higher than under water‐wet conditions under the slowest flow rate (Ca ∼ 9 × 10−6). Based on the visualization and scCO2 cluster analysis, we show that the scCO2 trapping process in our micromodels is governed by bypass trapping that is enhanced by the larger contact angle. Smaller contact angles enhance cooperative pore filling and widen brine fingers (or channels), leading to smaller volumes of scCO2 being bypassed. Increased flow rates suppress this wettability effect.
ImageCube: an image browser featuring a multi-dimensional data visualization technique

With the rapid development of the imaging technologies over the recent years, advanced visualization techniques for thousands of pictures are making big progress. At the same time, now we can obtain various sets of images which are called multi-dimensional or multivariate datasets via Internet. For example, we can obtain the images of recipes which have a variety of nutritional value, those of cars which have a variety of performance values, and those of medical which have a variety of diagnosis value, based on our specific requests. We think that image browsing techniques featuring multidimensional data visualization techniques are useful to explore such kinds of image datasets. Especially, multidimensional data visualization techniques are useful to explore and analyze features and structures in the datasets, including clusters, outliers or correlations. We think it is interesting to explore and analyze such features and structures of multidimensional values assigned to images while browsing the images themselves. Among various information visualization techniques, scatterplots is one of the most popular and widely-used visual representations for multidimensional data due to its simplicity, and visual clarity. Scatterplots visualize multidimensional datasets by assigning data dimensions to graphical axes and rendering data cases as points in the Cartesian space defined by the axes. This approach has been widely used in visualization technique such as Rolling the Dice [1], which presents new interactive methods to explore multidimensional data. It applies a metaphor of rolling a dice, since as they implement an animation mechanism as they transform one scatterplot representation into another one by rotating a cubic space. This poster proposes ”ImageCube”, an image browser featuring a multidimensional data visualization technique which is similar to Rolling the Dice. ImageCube can show the visualization through interactively selecting two dimensions from the multidimensional datasets of images applying scatterplot. Our implementation of ImageCube assists the dimension selection operations by suggesting interesting pairs of dimensions based on their correlations and entropies. ImageCube is helpful for users to obtain qualitative visualization results to explore and analyze features and structures of multidimensional values assigned to images. We tested ImageCube with images of recipes and those of cars. Visualization results in the poster demonstrate that ImageCube efficiently supports users to obtain insightful visualizations.
A New Sampling Protocol and Applications to Basing Cryptographic Primitives on the Hardness of NP

We investigate the question of what languages can be decided efficiently with the help of a recursive collision-finding oracle. Such an oracle can be used to break collision-resistant hash functions or, more generally, statistically hiding commitments. The oracle we consider, $\Sam_d$ where $d$ is the recursion depth, is based on the identically-named oracle defined in the work of Haitner et al. (FOCS '07). Our main result is a constant-round public-coin protocol ``$\AMSam$'' that allows an efficient verifier to emulate a $\Sam_d$ oracle for any constant depth $d = O(1)$ with the help of a $\BPP^\NP$ prover. $\AMSam$ allows us to conclude that if $L$ is decidable by a $k$-adaptive randomized oracle algorithm with access to a $\Sam_{O(1)}$ oracle, then $L \in \AM[k] \cap \coAM[k]$. The above yields the following corollary: assume there exists an $O(1)$-adaptive reduction that bases constant-round statistically hiding commitment on $\NP$-hardness, then $\NP \subseteq \coAM$ and the polynomial hierarchy collapses. The same result holds for any primitive that can be broken by $\Sam_{O(1)}$ including collision-resistant hash functions and $O(1)$-round oblivious transfer where security holds statistically for one of the parties. We also obtain non-trivial (though weaker) consequences for $k$-adaptive reductions for any $k = \poly(n)$. Prior to our work, most results in this research direction either applied only to non-adaptive reductions (\citeauthor{BogdanovT06}, SIAM J. of Comp. '06 and \citeauthor{AkaviaGGM06}, FOCS '06) or to one-way permutations (\citeauthor{Brassard79} FOCS '79). The main technical tool we use to prove the above is a new constant-round public-coin protocol ($\SWS$), which we believe to be of interest in its own right, that guarantees the following: given an efficient function $f$ on $n$ bits, let $D$ be the output distribution $D = f(U_n)$, then $\SWS$ allows an efficient verifier Arthur to use an all-powerful prover Merlin's help to sample a random $y \getsr D$ along with a good multiplicative approximation of the probability $p_y = \Pr_{y' \getsr D}[y' = y]$. The crucial feature of $\SWS$ is that it extends even to distributions of the form $D = f(U_\cs)$, where $U_\cs$ is the uniform distribution on an efficiently decidable subset $\cs \subseteq \zo^n$ (such $D$ are called efficiently samplable with \emph{post-selection}), as long as the verifier is also given a good approximation of the value $|\cs|$.
Efficient Isotropic BRDF Measurement

In this paper we present novel reflectance measurement procedures that require fewer total measurements than standard uniform sampling approaches. First, we acquire densely sampled reflectance data for a large collection of different materials. Using these densely sampled measurements we analyze the general surface reflectance function to determine the local signal variation at each point in the function's domain. We then use wavelet analysis to derive a common basis for all of the acquired reflectance functions as well as a corresponding non-uniform sampling pattern that corresponds to all non-zero wavelet coefficients. Second, we show that the reflectance of an arbitrary material can be represented as a linear combination of the surface reflectance functions. Furthermore, our analysis provides a reduced set of sampling points that permits us to robustly estimate the coefficients of this linear combination. These procedures dramatically shorten the acquisition time for isotropic reflectance measurements. We present a detailed description and analysis of our measurement approaches and sampling strategies.
Binary central stars of planetary nebulae

This paper reviews our knowledge on binary central stars of planetary nebulae and presents some personal opinions regarding their evolution. Three types of interactions are distinguished: type I, where the binary companion induces the mass loss; type II, where it shapes the mass loss but does not enhance it; type III, where a wide orbit causes the centre of mass to move, leading to a spiral embedded in the wind. Surveys for binary central stars are discussed, and the separations are compared to the distribution for binary post-AGB stars. The effect of close binary evolution on nebular morphology is discussed. Post-common-envelope binaries are surrounded by thin, expanding disks, expelled in the orbital plane. Wider binaries give rise to much thicker expanding torii. Type I binary evolution predicts a wide distribution of masses of central stars, skewed towards low masses. Comparison with observed mass distributions suggests that this is unlikely to be the only channel leading to the formation of a planetary nebula. A new sample of compact Bulge nebulae shows about 40% of nebulae with binary-induced morphologies.
Combinatorial Preconditioners for Scalar Elliptic Finite-Element Problems

We present a new preconditioner for linear systems arising from finite-element discretizations of scalar elliptic partial differential equations (PDE's). The solver splits the collection $\{K_{e}\}$ of element matrices into a subset of matrices that are approximable by diagonally dominant matrices and a subset of matrices that are not approximable. The approximable $K_{e}$'s are approximated by diagonally dominant matrices $L_{e}$'s that are assembled to form a global diagonally dominant matrix $L$. A combinatorial graph algorithm then approximates $L$ by another diagonally dominant matrix $M$ that is easier to factor. Finally, $M$ is added to the inapproximable elements to form the preconditioner, which is then factored. When all the element matrices are approximable, which is often the case, the preconditioner is provably efficient. Approximating element matrices by diagonally dominant ones is not a new idea, but we present a new approximation method which is both efficient and provably good. The splitting idea is simple and natural in the context of combinatorial preconditioners, but hard to exploit in other preconditioning paradigms. Experimental results show that on problems in which some of the $K_{e}$'s are ill conditioned, our new preconditioner is more effective than an algebraic multigrid solver, than an incomplete-factorization preconditioner, and than a direct solver.
The Reliability and Validity of Fatigue Measures During Short‐Duration Maximal‐Intensity Intermittent Cycling

&NA; Glaister, M. , M.H. Stone, A.M. Stewart, M. Hughes, and G.L. Moir. The reliability and validity of fatigue measures during short‐duration maximal‐intensity intermittent cycling. J. Strength Cond. Res. 18(3):459–462. 2004. —The purpose of the present study was to assess the reliability and validity of fatigue measures, as derived from 4 separate formulae, during tests of repeat sprint ability. On separate days over a 3‐week period, 2 groups of 7 recreationally active men completed 6 trials of 1 of 2 maximal (20 × 5 seconds) intermittent cycling tests with contrasting recovery periods (10 or 30 seconds). All trials were conducted on a friction‐braked cycle ergometer, and fatigue scores were derived from measures of mean power output for each sprint. Apart from formula 1, which calculated fatigue from the percentage difference in mean power output between the first and last sprint, all remaining formulae produced fatigue scores that showed a reasonably good level of test‐retest reliability in both intermittent test protocols (intraclass correlation range: 0.78–0.86; 95% likely range of true values: 0.54–0.97). Although between‐protocol differences in the magnitude of the fatigue scores suggested good construct validity, within‐protocol differences highlighted limitations with each formula. Overall, the results support the use of the percentage decrement score as the most valid and reliable measure of fatigue during brief maximal intermittent work.
New benchmark metrics for protein‐protein docking methods

With the development of many computational methods that predict the structural models of protein‐protein complexes, there is a pressing need to benchmark their performance. As was the case for protein monomers, assessing the quality of models of protein complexes is not straightforward. An effective scoring scheme should be able to detect substructure similarity and estimate its statistical significance. Here, we focus on characterizing the similarity of the interfaces of the complex and introduce two scoring functions. The first, the interfacial Template Modeling score (iTM‐score), measures the geometric distance between the interfaces, while the second, the Interface Similarity score (IS‐score), evaluates their residue‐residue contact similarity in addition to their geometric similarity. We first demonstrate that the IS‐score is more suitable for assessing docking models than the iTM‐score. The IS‐score is then validated in a large‐scale benchmark test on 1562 dimeric complexes. Finally, the scoring function is applied to evaluate docking models submitted to the Critical Assessment of Prediction of Interactions (CAPRI) experiments. While the results according to the new scoring scheme are generally consistent with the original CAPRI assessment, the IS‐score identifies models whose significance was previously underestimated. Proteins 2011. © 2011 Wiley‐Liss, Inc.
A new look at the statistical model identification

The history of the development of statistical hypothesis testing in time series analysis is reviewed briefly and it is pointed out that the hypothesis testing procedure is not adequately defined as the procedure for statistical model identification. The classical maximum likelihood estimation procedure is reviewed and a new estimate minimum information theoretical criterion (AIC) estimate (MAICE) which is designed for the purpose of statistical identification is introduced. When there are several competing models the MAICE is defined by the model and the maximum likelihood estimates of the parameters which give the minimum of AIC defined by AIC = (-2)log-(maximum likelihood) + 2(number of independently adjusted parameters within the model). MAICE provides a versatile procedure for statistical model identification which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure. The practical utility of MAICE in time series analysis is demonstrated with some numerical examples.
Three-Phase Multi-pulse Converter Based on FPGA

—The voltage source converter topology has gained wide acceptance for applications in electric power generation, motor drives, computer's power adapters, uninterruptible power supplies, flexible ac transmission systems, and alternative energy production systems. Therefore, it is necessary to understand clearly how they work and explore control techniques to improve its performance characteristics. This paper is aimed to present the analysis of steady state converter operation in laboratory prototype. The device is based on full bridge with twelve insulated gate bipolar transistor, including independent trigger signal for each element. The sinusoidal pulse width modulation technique is employed for regulating purpose programmed on FPGA. Finally, a comparison between digital simulations and experimental results is presented. The resultant alternating current waveform has a very well quality shape.
Scalable Parallel Solution Techniques for Data-Intensive Problems in Distributed Memory

Computational science and engineering has traditionally been comprised of linear algebra problems induced by large systems of PDEs. These problems often possess underlying natural locality which can be determined analytically, often via static analysis. An increasingly important class of data-intensive applications is emerging that lacks this natural, or domain-induced, locality. Rather than being analytically deducible, the dependency structure of this class of computations is determined by the input data itself. This data-carried dependency structure is expressed at run time and offers limited opportunities for static analysis. These computations benefit from a variety of fine-grained and dynamic solution techniques well suited to the irregular and non-local nature of these problems.
Flexible Clustered Multi-Task Learning by Learning Representative Tasks

Multi-task learning (MTL) methods have shown promising performance by learning multiple relevant tasks simultaneously, which exploits to share useful information across relevant tasks. Among various MTL methods, clustered multi-task learning (CMTL) assumes that all tasks can be clustered into groups and attempts to learn the underlying cluster structure from the training data. In this paper, we present a new approach for CMTL, called flexible clustered multi-task (FCMTL), in which the cluster structure is learned by identifying representative tasks. The new approach allows an arbitrary task to be described by multiple representative tasks, effectively soft-assigning a task to multiple clusters with different weights. Unlike existing counterpart, the proposed approach is more flexible in that (a) it does not require clusters to be disjoint, (b) tasks within one particular cluster do not have to share information to the same extent, and (c) the number of clusters is automatically inferred from data. Computationally, the proposed approach is formulated as a row-sparsity pursuit problem. We validate the proposed FCMTL on both synthetic and real-world data sets, and empirical results demonstrate that it outperforms many existing MTL methods.
Information Technology and Quantitative Management ( ITQM 2015 ) Time Series Prediction using Restricted Boltzmann Machines and Backpropagation

Time series prediction appear in many real-world problems, e.g., financial market, signal processing, weather forecasting among others. The underlying models and time series data of those problems are generally complex in a way that reasonable accurate estimation cannot be easily achieved, thus requiring more advanced techniques. Statistical models are the classical approaches for tackling this problem. Many works extended different architectures of Artificial neural networks to work with time series prediction, such as Feedforward, Boltzmann Machines and Deep Belief Network. A Deep Belief Network based on hybridization between Gaussian-Bernoulli Restricted Boltzmann Machine and the Backpropagation algorithm is presented. The hybrid algorithm is tested on three time series databases showing promising results. c © 2015 The Authors. Published by Elsevier B.V. Selection and/or peer-review under responsibility of ITQM2015.
Maximal functional electrical stimulation in routine practice

Maximal functional electrical stimulation is now an established treatment for urgency and urge incontinence. Many studies have been presented with good and consistent results. In a number of prospective studies we have previously recorded very favourable effects in stress incontinence and urge incontinence. In the present study, we have compared our previous experience with a retrospective analysis of a series of maximal functional electrical stimulation given according to a simple routine protocol and including 84 patients.
Why don't patients with diagnosed diabetes attend a free 'Get Checked' annual review?

INTRODUCTION A key strategy for improving the management of patients with diabetes is the provision of a free annual review 'Get Checked'. Although it is known that certain patients do not attend these free reviews, little is known about the barriers. METHODS A group of patients with diabetes who had not attended an annual review in the previous two years were identified and sent questionnaires asking about the barriers to attending. Non-respondents where followed up with a telephone call. Barriers were thematically analysed. FINDINGS 26/68 patients identified patients responded (38%). Key issues identified included difficulty with transport, conflict with work and lack of motivation. There were differences in responses between Maori and non-Maori. CONCLUSION Recommendations include more emphasis in recognising Maori tikanga (culture), more flexible provision of services to allow working patients to attend and increased emphasis on reminders for patients.