Miracle-dz/UniFAR-FTUs huggingface dataset:
Intra-individual daily and yearly variability in actigraphically recorded sleep measures: the CARDIA study.

STUDY OBJECTIVES To describe the day-to-day and year-to-year variation in sleep characteristics among early middle-aged adults. DESIGN Participants wore an Actiwatch (Mini Mitter, Inc) for 3 days on two occasions approximately 1 year apart. PARTICIPANTS N = 669 participants aged 38-50 years from the Chicago site of the Coronary Artery Risk Development in Young Adults (CARDIA) cohort study. MEASUREMENTS AND RESULTS Sleep measures included sleep duration, sleep latency, sleep efficiency, and time in bed. For each sleep parameter, total variance was decomposed into between-subject variance, within-subject variance from day to day, and within-subject variance from year to year. The standard deviation was calculated from the variance. Analysis yielded a within-subject daily standard deviation (SD) of 1.26 hours and a within-subject yearly SD of 0.39 hours for sleep duration. Daily SD was 30.7 minutes and yearly SD was 6.3 minutes for within-subject variability of sleep latency. Daily SD was 8.4% and yearly SD was 2.7% for within-subject variability of sleep efficiency. Finally, daily SD was 1.31 hours and yearly SD was 0.52 hours for within-subject variability of time in bed. CONCLUSIONS For each of the 4 sleep characteristics, nightly variability was much greater than yearly variability, meaning sleep behavior changes little in one year in this cohort of early middle-aged adults, despite large daily fluctuations. These results have important methodological implications, including that single-day measures of sleep may not accurately reflect habitual behavior.
Design of MIMO Communication Systems Using Tapped Delay Line Structure in Receiver Side

SUMMARY This paper presents a simple method to determine weights of single carrier multiple input multiple output (MIMO) broadband communication systems adopting tapped delay line (TDL) structure in receiver side for the effective communication under frequency selective fading (FSF) environment. First, assuming the perfect knowledge of the channel matrix in both arrays, an iterative design method of transmitter and receiver weights is proposed. In this approach, both weights are determined alternately to maximize signal to noise plus interference ratio (SINR) by fixing the weight of one side while optimizing the other, and this operation is repeated until SINR converges. Next, considering the case of uninformed transmitter, maximum SINR design method of MIMO system is extended for space time block coding (STBC) scheme working under FSF. Through computer simulations, it is demonstrated that the proposed schemes achieves higher SINR than conventional method with delay-less structure, particularly for the fading with long duration.
The time course of altered brain activity during 7-day simulated microgravity

Microgravity causes multiple changes in physical and mental levels in humans, which can induce performance deficiency among astronauts. Studying the variations in brain activity that occur during microgravity would help astronauts to deal with these changes. In the current study, resting-state functional magnetic resonance imaging (rs-fMRI) was used to observe the variations in brain activity during a 7-day head down tilt (HDT) bed rest, which is a common and reliable model for simulated microgravity. The amplitudes of low frequency fluctuation (ALFF) of twenty subjects were recorded pre-head down tilt (pre-HDT), during a bed rest period (HDT0), and then each day in the HDT period (HDT1–HDT7). One-way analysis of variance (ANOVA) of the ALFF values over these 8 days was used to test the variation across time period (p < 0.05, corrected). Compared to HDT0, subjects presented lower ALFF values in the posterior cingulate cortex (PCC) and higher ALFF values in the anterior cingulate cortex (ACC) during the HDT period, which may partially account for the lack of cognitive flexibility and alterations in autonomic nervous system seen among astronauts in microgravity. Additionally, the observed improvement in function in CPL during the HDT period may play a compensatory role to the functional decline in the paracentral lobule to sustain normal levels of fine motor control for astronauts in a microgravity environment. Above all, those floating brain activities during 7 days of simulated microgravity may indicate that the brain self-adapts to help astronauts adjust to the multiple negative stressors encountered in a microgravity environment.
Optimal Multiple Intervals Discretization of Continuous Attributes for Supervised Learning

In this paper, we propose an extension of Fischer's algorithm to compute the optimal discretization of a continuous variable in the context of supervised learning. Our algorithm is extremely performant since its only depends on the number of runs and not directly on the number of points of the sample data set. We propose an empirical comparison between the optimal algorithm and two hill climbing heuristics.
Emulating grid cell spatial cognition in an FPGA

This paper presents a unique neurobiological inspired architecture for mobile robot environment mapping. The target of this mapping architecture is not to create a new mapping system that out performs current state of the art systems. It, however, is an attempt to develop a cognitive map that is based on the grid cell, which is found in the brain (entorhinal cortex) of rodents and other mammals, and is used for spatial cognition in navigation. The hexagonal lattice firing locations of a single grid cell will be emulated in a field programmable gate array silicon chip as individual logic and data storage firing nodes, as well as a central grid cell node. The firing nodes will be used for mapping and will work in parallel to actively aid in route planning. Thus, creating some level of spatial awareness in silicon.
Numerical Analysis of Semi-transverse Ventilation of Extra-long Road Tunnel

Er Lang Shan tunnel is the most absolute altitude highway tunnel in china, which was firstly used the semi-transverse ventilation system, is characteristic of extensive length, higher absolute altitude, multivariate climate and complex wind stream. Based on one-dimensional fluid mathematic models, the characteristics of distribution of wind field were simulated under diversity conditions such as fans, transportation stream and natural pressure. The maximal capability of process of vehicle jam under increase of fans and vehicle was also analyzed.
From Story Points to COSMIC Function Points in Agile Software Development - A Six Sigma perspective

The spreading of agile methodologies in software development raises the question of how to measure requirements once more, as it happened in ‘traditional’ software industry development approaches decades ago. The difference is that requirements are not known in advance but detected as User Stories while iterating and enhancing the software product from one agile ‘Sprint’ to the other. Some authors – promoting best practices for agile software development – propose Story Points to size User Stories (e.g., Scrum, with Story Cards), yet not combined with base project estimation. Story Points are not standardized, thus leading to eventual misconceptions and quantitative differences among practitioners and domains. The uncertainty implied in such approach can therefore propagate to any estimate based on it, not to mention the difficulty in accurately tracing requirements and their variation over the project and across project iterations. This work investigates benefits from adopting a standardized Functional Size Measurement (FSM) method, such as COSMIC Function Points, in place of Story Points. Using a Transfer Function (from the Six Sigma practice) that transforms size into effort spent within a particular agile team, defect density prediction can be made using sensitivity analysis.
Real business cycles in emerging economies: the role of international growth and interest rate

T his paper is aimed at developing a business-cycle model for a small open emerging economy (SOEE). The model is parameterized, calibrated, and simulated to rationalize two important stylized facts in a SOEE. The first one is that when the international interest rate increases, the growth rate of a soee is reduced. Secondly, when industrialized countries are in recession, a soee suffers an even larger reduction in their growth rate. The obtained results show that if exports respond negatively to the international interest rate or exports are reduced due to an international recession, the aggregated consumption of the domestic economy is substantially more volatile than an economy where exports do not react. Moreover, this paper provides a possible explanation to the puzzle that developing countries suffer a recession not only when industrialized countries are in recession, but also when they are growing too fast.
Human action recognition using sparse representation

Sparse representation has been applied recently to many signal processing and computer vision and demonstrated successful results. Inspired by them, we propose an action recognition approach based on sparse representation to avoid the sensitivity of parameter selection in nearest-neighbor classification method and improve the discriminative capability. Firstly, each frame in the test sequence is treated as a sparse linear combination of all frames in the training sequences, and its sparsest representation is computed by L1-minimization. Then each frame is classified by minimizing the residual. Finally, we classify the testing sequence based on the majority of these frames' classes. Experiments are conducted on two publicly availabe datasets: Weizmann dataset and IXMAS multiview dataset. The results demonstrate that our approach achieves better performance than nearest-neighbor, and outperforms most recently proposed methods.
Simulation analysis of distance-aware graph-based semi-supervised learning

According to the problem of agglomeration effect of Graph-based Semi-Supervised Learning (G-SSL), this paper studies a Distance-aware Graph-based Semi-supervised Learning (DG-SSL) algorithm, which reduces the agglomeration effect of G-SSL, and holds smaller average estimation error. When compared with the K nearest neighbors (KNN) algorithm, moreover, the DG-SS algorithm can achieve better positioning result by using a small number of labeled samples. Simulation results show that the DG-SSL algorithm effectively resolve the problem of requiring enough labeled samples for Radio Map setup in indoor positioning algorithm. Thus, it reduces the workload and expenditure of establishing the Radio Map.
Pegasus: Coordinated Scheduling for Virtualized Accelerator-based Systems

Heterogeneous multi-cores--platforms comprised of both general purpose and accelerator cores--are becoming increasingly common. While applications wish to freely utilize all cores present on such platforms, operating systems continue to view accelerators as specialized devices. The Pegasus system described in this paper uses an alternative approach that offers a uniform resource usage model for all cores on heterogeneous chip multiprocessors. Operating at the hypervisor level, its novel scheduling methods fairly and efficiently share accelerators across multiple virtual machines, thereby making accelerators into first class schedulable entities of choice for many-core applications. Using NVIDIA GPGPUs coupled with x86-based general purpose host cores, a Xen-based implementation of Pegasus demonstrates improved performance for applications by better managing combined platform resources. With moderate virtualization penalties, performance improvements range from 18% to 140% over base GPU driver scheduling when the GPUs are shared.
Automated Induction of Heterogeneous Proximity Measures for Supervised Spectral Embedding

Spectral embedding methods have played a very important role in dimensionality reduction and feature generation in machine learning. Supervised spectral embedding methods additionally improve the classification of labeled data, using proximity information that considers both features and class labels. However, these calculate the proximity information by treating all intraclass similarities homogeneously for all classes, and similarly for all interclass samples. In this paper, we propose a very novel and generic method which can treat all the intra- and interclass sample similarities heterogeneously by potentially using a different proximity function for each class and each class pair. To handle the complexity of selecting these functions, we employ evolutionary programming as an automated powerful formula induction engine. In addition, for computational efficiency and expressive power, we use a compact matrix tree representation equipped with a broad set of functions that can build most currently used similarity functions as well as new ones. Model selection is data driven, because the entire model is symbolically instantiated using only problem training data, and no user-selected functions or parameters are required. We perform thorough comparative experimentations with multiple classification datasets and many existing state-of-the-art embedding methods, which show that the proposed algorithm is very competitive in terms of classification accuracy and generalization ability.
Activity-Dependent Autocrine-Paracrine Activation of Neuronal P2Y Receptors

Activation of P2Y receptors by released nucleotides subserves important autocrine-paracrine functions in various non-neural tissues. To investigate how P2Y receptors are activated in a neuronal environment, we used PC12 cells in which nucleotides were found to elicit increases in inositol phosphates via P2Y2 and decreases in cAMP via P2Y12 receptors. Depolarization of PC12 cells raised inositol phosphates, and blockade of voltage-gated Ca2+ channels by Cd2+ or degradation of extracellular nucleotides by apyrase prevented this effect. In nondepolarized cells, apyrase did not affect inositol phosphates. Depolarization of PC12 cells also reduced the A2A receptor-mediated synthesis of cAMP. This effect was again prevented by Cd2+ or apyrase, but apyrase enhanced the synthesis of cAMP even in nondepolarized cells. Overexpression of rat P2Y2 receptors increased the nucleotide-dependent inositol phosphate accumulation and enhanced the effect of K+ depolarization. Nevertheless, apyrase still failed to alter spontaneous inositol phosphate accumulation. Expression of rat P2Y1 receptors, in contrast, led to huge increases in spontaneous inositol phosphate accumulation, which was reduced by a receptor antagonist or by apyrase. This increased synthesis of inositol phosphates could not be further enhanced by depolarization or receptor agonists, but when endogenous nucleotides were removed by superfusion, recombinant P2Y1 receptors could be activated to mediate an inhibition of M-type K+ channels. These results indicate that nucleoside diphosphate-sensitive (P2Y12 and P2Y1) receptors are activated by spontaneous nucleotide release, whereas triphosphate-sensitive (P2Y2) receptors require an excess of depolarization-evoked release to become activated.
Assessing Website Pharmacy Drug Quality: Safer Than You Think?

Background Internet-sourced drugs are often considered suspect. The World Health Organization reports that drugs from websites that conceal their physical address are counterfeit in over 50 percent of cases; the U.S. Food and Drug Administration (FDA) works with the National Association of Boards of Pharmacy (NABP) to regularly update a list of websites likely to sell drugs that are illegal or of questionable quality. Methods and Findings This study examines drug purchasing over the Internet, by comparing the sales of five popular drugs from a selection of websites stratified by NABP or other ratings. The drugs were assessed for price, conditions of purchase, and basic quality. Prices and conditions of purchase varied widely. Some websites advertised single pills while others only permitted the purchase of large quantities. Not all websites delivered the exact drugs ordered, some delivered no drugs at all; many websites shipped from multiple international locations, and from locations that were different from those advertised on the websites. All drug samples were tested against approved U.S. brand formulations using Raman spectrometry. Many (17) websites substituted drugs, often in different formulations from the brands requested. These drugs, some of which were probably generics or perhaps non-bioequivalent copy versions, could not be assessed accurately. Of those drugs that could be assessed, none failed from “approved”, “legally compliant” or “not recommended” websites (0 out of 86), whereas 8.6% (3 out of 35) failed from “highly not recommended” and unidentifiable websites. Conclusions Of those drugs that could be assessed, all except Viagra® passed spectrometry testing. Of those that failed, few could be identified either by a country of manufacture listed on the packaging, or by the physical location of the website pharmacy. If confirmed by future studies on other drug samples, then U.S. consumers should be able to reduce their risk by relying on credentialing agencies recommended lists and by using common sense when examining packaging and pills.
New model diagnostics for spatio-temporal systems in epidemiology and ecology

A cardinal challenge in epidemiological and ecological modelling is to develop effective and easily deployed tools for model assessment. The availability of such methods would greatly improve understanding, prediction and management of disease and ecosystems. Conventional Bayesian model assessment tools such as Bayes factors and the deviance information criterion (DIC) are natural candidates but suffer from important limitations because of their sensitivity and complexity. Posterior predictive checks, which use summary statistics of the observed process simulated from competing models, can provide a measure of model fit but appropriate statistics can be difficult to identify. Here, we develop a novel approach for diagnosing mis-specifications of a general spatio-temporal transmission model by embedding classical ideas within a Bayesian analysis. Specifically, by proposing suitably designed non-centred parametrization schemes, we construct latent residuals whose sampling properties are known given the model specification and which can be used to measure overall fit and to elicit evidence of the nature of mis-specifications of spatial and temporal processes included in the model. This model assessment approach can readily be implemented as an addendum to standard estimation algorithms for sampling from the posterior distributions, for example Markov chain Monte Carlo. The proposed methodology is first tested using simulated data and subsequently applied to data describing the spread of Heracleum mantegazzianum (giant hogweed) across Great Britain over a 30-year period. The proposed methods are compared with alternative techniques including posterior predictive checking and the DIC. Results show that the proposed diagnostic tools are effective in assessing competing stochastic spatio-temporal transmission models and may offer improvements in power to detect model mis-specifications. Moreover, the latent-residual framework introduced here extends readily to a broad range of ecological and epidemiological models.
Fuzzy ontology constructing and its application in traditional Chinese medicine

In ontology, domain knowledge is formally expressed by concepts that both human and machine can understand. These concepts include entity, attribute, relation and truth, etc. It is used as a standard knowledge representation for the Semantic Web. Nowadays, most of ontology is used to describe concepts and relations quantitatively. However, the concepts and relations are fuzzy and uncertain in many application areas. The classical ontology could not represent information effectively. A feasible solution of this problem is to introduce Fuzzy Logic into ontology to process uncertain information. In this paper, the structural description and building process of fuzzy ontology and the reasoning method based on fuzzy ontology are proposed. The application of the method in the traditional Chinese medicine (TCM) field is given.
Ages of Globular Clusters: Breaking the Age-Distance Degeneracy with the Luminosity Function

We extend our previous method to determine globular cluster (GC) ages using the luminosity function (Jimenez & Padoan). This method provides at the same time independent determinations of distance and age of a GC, by simply counting the number of stars found inside specified luminosity bins. The main uncertainties in other traditional methods for determining GC ages are absent (e.g., mixing length, color-Teff calibration, morphology of the color-magnitude diagram). If GC stellar counts with statistical errors not larger than 3% are available, the age can be determined with an uncertainty of about 0.5 Gyr, and the distance modulus with an uncertainty of about 0.06 mag.
Education for Ward Nurses Influences the Quality of Inpatient's Bowel Preparation for Colonoscopy

AbstractAlthough adequate bowel preparation is a prerequisite for colonoscopy, preparation among inpatients is often suboptimal. This study aimed to evaluate the impact of ward nurse education on the quality of bowel preparation of inpatients.A prospective, double-blinded, non-randomized, controlled study was performed. Expert endoscopists provided enhanced education to nurses who belonged to an “educated ward” followed by training that was repeated every week for 1 month. The primary outcome was the quality of the bowel preparation, which was based on the Ottawa Bowel Preparation Scale (OBPS). Patient compliance and their subjective feelings and the factors affecting inadequate bowel preparation were also analyzed.One hundred three inpatients in the educated ward and 102 patients in the control ward were enrolled. Baseline data were comparable between the 2 wards. The mean values of the total OBPS scores were 4.42 ± 2.23 and 6.15 ± 2.38 in the educated and control wards, respectively (P < 0.001). The rate of poor preparation (OBPS ≥ 6) in the educated ward was significantly lower than that in the control ward (31.1% vs 58.8%, P < 0.001). Compliance with preparation and diet instructions in the educated ward was superior to that in the control ward (P<0.001). Control patients were more likely to be anxious before colonoscopy (P < 0.001), whereas patients in the educated ward showed higher level of satisfaction (P = 0.001) and better sleep quality (P < 0.001). A lack of ward nurse education (OR 2.365, P = 0.025), constipation (OR 6.517, P < 0.001), and insufficient water ingestion (OR 2.044, P = 0.042) were independently associated with inadequate bowel preparation among inpatients.Ward nurse education effectively improved the quality of bowel preparation, and relevant colonoscopic outcomes among inpatients. Additional efforts are needed to control constipation and to encourage additional water ingestion in inpatients for better bowel preparation.
An empirical study on clustering for isolating bugs in fault localization

Spectrum-based Fault Localization (SBFL) techniques use risk evaluation formulas to calculate each statement's likelihood of having a bug based on test results. SBFL can not only be used in statement level, but also can be used with other program entities such as branches, functions and so on. Most previous studies have been conducted under the assumption of a single bug. However, software always contains multi-bugs in practice. A natural idea of debugging is to isolate bugs and then use SBFL techniques to locate one bug for each group. In this paper, we conduct an empirical study on clustering for isolating bugs in fault localization. We analyze the effects of six fault localization techniques and two cluster algorithms. The main observations are: (1) ER5 (Wong1) achieves the best results of fault localization with clustering; (2) K-means outperforms hierarchical clustering for isolating bugs in fault localization.