Miracle-dz/UniFAR-FTUs huggingface dataset:
Derivation and Validation of a Model to Predict Daily Risk of Death in Hospital

BackgroundAs electronic patient data from automated hospital databases become increasingly available, it is important to explore the ways in which these data could be used for the purposes other than patient care, such as quality assurance and improvement. ObjectiveTo determine if information from automated patient databases can be used to derive a model that can predict patients' daily risk of death in hospital. Such a model could be used to improve the ability to risk-adjust hospital mortality rates. Study Design and SettingRetrospective cohort study of 159,794 hospitalizations at The Ottawa Hospital between April 1, 2004 and March 31, 2009. The model was derived using time-dependent Cox regression methods on a random two-thirds of admissions. The model was validated by applying the coefficients to the other third of admissions. ResultsInpatient mortality was 5%. The final model included: patient age; admission type; intensive care unit status; alternative level of care status; and separate scores for patient comorbidity, in-hospital procedures, and acute illness (using information from 14 laboratory tests). In the validation set, the model had excellent discrimination (c-statistic 0.879, 95% confidence interval: 0.872-0.886) and calibration in all risk strata over all admission days. ConclusionWe found that information from our hospital's automated patient databases could be used to accurately predict patients' daily risk of death in hospital. The predictions from this model could be used in quality of care analyses to more accurately risk-adjust hospital mortality rates and by hospitals to improve triage processes and patient flow.
Commutativity analysis for software parallelization: letting program transformations see the big picture

Extracting performance from many-core architectures requires software engineers to create multi-threaded applications, which significantly complicates the already daunting task of software development. One solution to this problem is automatic compile-time parallelization, which can ease the burden on software developers in many situations. Clearly, automatic parallelization in its present form is not suitable for many application domains and new compiler analyses are needed address its shortcomings. In this paper, we present one such analysis: a new approach for detecting commutative functions. Commutative functions are sections of code that can be executed in any order without affecting the outcome of the application, e.g., inserting elements into a set. Previous research on this topic had one significant limitation, in that the results of a commutative functions must produce identical memory layouts. This prevented previous techniques from detecting functions like malloc, which may return different pointers depending on the order in which it is called, but these differing results do not affect the overall output of the application. Our new commutativity analysis correctly identify these situations to better facilitate automatic parallelization. We demonstrate that this analysis can automatically extract significant amounts of parallelism from many applications, and where it is ineffective it can provide software developers a useful list of functions that may be commutative provided semantic program changes that are not automatable.
Reproductive isolation and patterns of genetic differentiation in a cryptic butterfly species complex

Molecular studies of natural populations are often designed to detect and categorize hidden layers of cryptic diversity, and an emerging pattern suggests that cryptic species are more common and more widely distributed than previously thought. However, these studies are often decoupled from ecological and behavioural studies of species divergence. Thus, the mechanisms by which the cryptic diversity is distributed and maintained across large spatial scales are often unknown. In 1988, it was discovered that the common Eurasian Wood White butterfly consisted of two species (Leptidea sinapis and Leptidea reali), and the pair became an emerging model for the study of speciation and chromosomal evolution. In 2011, the existence of a third cryptic species (Leptidea juvernica) was proposed. This unexpected discovery raises questions about the mechanisms preventing gene flow and about the potential existence of additional species hidden in the complex. Here, we compare patterns of genetic divergence across western Eurasia in an extensive data set of mitochondrial and nuclear DNA sequences with behavioural data on inter‐ and intraspecific reproductive isolation in courtship experiments. We show that three species exist in accordance with both the phylogenetic and biological species concepts and that additional hidden diversity is unlikely to occur in Europe. The Leptidea species are now the best studied cryptic complex of butterflies in Europe and a promising model system for understanding the formation of cryptic species and the roles of local processes, colonization patterns and heterospecific interactions for ecological and evolutionary divergence.
Synaptic and nonsynaptic plasticity approximating probabilistic inference

Learning and memory operations in neural circuits are believed to involve molecular cascades of synaptic and nonsynaptic changes that lead to a diverse repertoire of dynamical phenomena at higher levels of processing. Hebbian and homeostatic plasticity, neuromodulation, and intrinsic excitability all conspire to form and maintain memories. But it is still unclear how these seemingly redundant mechanisms could jointly orchestrate learning in a more unified system. To this end, a Hebbian learning rule for spiking neurons inspired by Bayesian statistics is proposed. In this model, synaptic weights and intrinsic currents are adapted on-line upon arrival of single spikes, which initiate a cascade of temporally interacting memory traces that locally estimate probabilities associated with relative neuronal activation levels. Trace dynamics enable synaptic learning to readily demonstrate a spike-timing dependence, stably return to a set-point over long time scales, and remain competitive despite this stability. Beyond unsupervised learning, linking the traces with an external plasticity-modulating signal enables spike-based reinforcement learning. At the postsynaptic neuron, the traces are represented by an activity-dependent ion channel that is shown to regulate the input received by a postsynaptic cell and generate intrinsic graded persistent firing levels. We show how spike-based Hebbian-Bayesian learning can be performed in a simulated inference task using integrate-and-fire (IAF) neurons that are Poisson-firing and background-driven, similar to the preferred regime of cortical neurons. Our results support the view that neurons can represent information in the form of probability distributions, and that probabilistic inference could be a functional by-product of coupled synaptic and nonsynaptic mechanisms operating over several timescales. The model provides a biophysical realization of Bayesian computation by reconciling several observed neural phenomena whose functional effects are only partially understood in concert.
On efficient wear leveling for large-scale flash-memory storage systems

Flash memory won its edge over many other storage media for embedded systems, because it provides better tolerance to the extreme environments which embedded systems are exposed to. In this paper, techniques referred to as wear leveling for the lengthening of flash-memory overall lifespan are considered. This paper presents the dual-pool algorithm, which realizes two key ideas: To cease the wearing of blocks by storing cold data, and to smartly leave alone blocks until wear leveling takes effect. The proposed algorithm requires no complicated tuning, and it resists changes of spatial locality in workloads. Extensive evaluation and comparison were conducted, and the merits of the proposed algorithm are justified in terms of wear-leveling performance and resource conservation.
Sampling-based Multilingual Alignment

We present a sub-sentential alignment method that extracts high quality multi-word alignments from sentence-aligned multilingual parallel corpora. Unlike other methods, it exploits low frequency terms, which makes it highly scalable. As it relies on alingual concepts, it can process any number of languages at once. Experiments have shown that it is competitive with state-of-the-art methods.
(S)neutrino properties in {ital R}-parity-violating supersymmetry: {ital CP}-conserving phenomena

{ital R}-parity-violating supersymmetry (with a conserved baryon number {ital B}) provides a framework for particle physics with lepton-number- ({ital L}-) violating interactions. We examine in detail the structure of the most general {ital R}-parity-violating ({ital B}-conserving) model of low-energy supersymmetry. We analyze the mixing of Higgs bosons with sleptons and the mixing of charginos and neutralinos with charged leptons and neutrinos, respectively. Implications for neutrino and sneutrino masses and mixing and {ital CP}-conserving sneutrino phenomena are considered. {ital L}-violating low-energy supersymmetry can be probed at future colliders by studying the phenomenology of sneutrinos. Sneutrino-antisneutrino mass splittings and lifetime differences can provide new opportunities to probe lepton number violation at colliders. {copyright} {ital 1999} {ital The American Physical Society}
Receptor Salvage from the Prevacuolar Compartment Is Essential for Efficient Vacuolar Protein Targeting

We have characterized the requirements to inhibit the function of the plant vacuolar sorting receptor BP80 in vivo and gained insight into the crucial role of receptor recycling between the prevacuolar compartment and the Golgi apparatus. The drug wortmannin interferes with the BP80-mediated route to the vacuole and induces hypersecretion of a soluble BP80-ligand. Wortmannin does not prevent receptor-ligand binding itself but causes BP80 levels to be limiting. Consequently, overexpression of BP80 partially restores vacuolar cargo transport. To simulate receptor traffic, we tested a truncated BP80 derivative in which the entire lumenal domain of BP80 has been replaced by the green fluorescent protein (GFP). The resulting chimeric protein (GFP-BP80) accumulates in the prevacuolar compartment as expected, but a soluble GFP fragment can also be detected in purified vacuoles. Interestingly, GFP-BP80 coexpression interferes with the correct sorting of a BP80-ligand and causes hypersecretion that is reversible by expressing a 10-fold excess of full-length BP80. This suggests that GFP-BP80 competes with endogenous BP80 mainly at the retrograde transport route that rescues receptors from the prevacuolar compartment. Treatment with wortmannin causes further leakage of GFP-BP80 from the prevacuolar compartment to the vacuoles, whereas BP80-ligands are secreted. We propose that recycling of the vacuolar sorting receptor from the prevacuolar compartment to the Golgi apparatus is an essential process that is saturable and wortmannin sensitive.
A comparative study of sound localization algorithms for energy aware sensor network nodes

Sound localization using energy-aware hardware for sensor networks nodes is a problem with many applications in surveillance and security. In this paper, we evaluate four algorithms for sound localization using signals recorded in a natural environment with an array of commercial off-the-shelf microelectromechanical systems microphones and a specially designed compact acoustic enclosure. We evaluate performance of the algorithms and their hardware complexity which relates directly to energy consumption.
Absorption and pharmacokinetics of green tea catechins in beagles

The present study evaluates for the first time in dogs, the kinetics of green tea catechins and their metabolic forms in plasma and urine. Ten beagles were administered 173 mg (12·35 mg/kg body weight) of catechins as a green tea extract, in capsules. Blood samples were collected during 24 h after intake and urine samples were collected during the following periods of time: 0–2, 2–6, 6–8 and 8–24 h. Two catechins with a galloyl moiety and three conjugated metabolites were detected in plasma. Most of the detected forms in plasma reached their maximum plasma concentration (Cmax) at around 1 h. Median Cmax for ( − )-epigallocatechin-3-gallate (EGCG), ( − )-epicatechin-3-gallate (ECG), ( − )-epigallocatechin glucuronide (EGC-glucuronide), ( − )-epicatechin glucuronide (EC-glucuronide), ( − )-epicatechin sulphate (EC-sulphate) were 0·3 (range 0·1–1·9), 0·1 (range 0–0·4), 0·8 (range 0·2–3·9), 0·2 (range 0·1–1·7) and 1 (range 0·3–3·4) μmol/l, respectively. The areas under the plasma concentration v. time curves (AUC0 → 24) were 427 (range 102–1185) μmol/l × min for EGC-glucuronide, 112 (range 53–919) μmol/l × min for EC-sulphate, 71 (range 26–306) μmol/l × min for EGCG, 40 (range 12–258) μmol/l × min for EC-glucuronide and 14 (range 0·1–124) μmol/l × min for ECG. The values of mean residence time (MRT0 → 24) were 5 (range 2–16), 2 (range 1–11), 10 (range 2–13), 3 (range 2–16) and 2·4 (range 1–18) h for EGCG, ECG, EGC-glucuronide, EC-glucuronide and EC-sulphate, respectively. In urine, catechins were present as conjugated forms, suggesting bile excretion of EGCG and ECG. Green tea catechins are absorbed following an oral administration and EGC-glucuronide is the metabolic form that remains in the organism for a longer period of time, suggesting that this compound could suffer an enterohepatic cycle.
The impact of aerosol hygroscopic growth on the single-scattering albedo and its application on the NO 2 photolysis rate coefficient

Abstract. Hygroscopic growth of aerosol particles can significantly affect their single-scattering albedo (ω), and consequently alters the aerosol effect on tropospheric photochemistry. In this study, the impact of aerosol hygroscopic growth on ω and its application to the NO2 photolysis rate coefficient (JNO2) are investigated for a typical aerosol particle population in the North China Plain (NCP). The variations of aerosol optical properties with relative humidity (RH) are calculated using a Mie theory aerosol optical model, on the basis of field measurements of number–size distribution and hygroscopic growth factor (at RH values above 90%) from the 2009 HaChi (Haze in China) project. Results demonstrate that ambient ω has pronouncedly different diurnal patterns from ω measured at dry state, and is highly sensitive to the ambient RHs. Ambient ω in the NCP can be described by a dry state ω value of 0.863, increasing with the RH following a characteristic RH dependence curve. A Monte Carlo simulation shows that the uncertainty of ω from the propagation of uncertainties in the input parameters decreases from 0.03 (at dry state) to 0.015 (RHs > 90%). The impact of hygroscopic growth on ω is further applied in the calculation of the radiative transfer process. Hygroscopic growth of the studied aerosol particle population generally inhibits the photolysis of NO2 at the ground level, whereas accelerates it above the moist planetary boundary layer. Compared with dry state, the calculated JNO2 at RH of 98% at the height of 1 km increases by 30.4%, because of the enhancement of ultraviolet radiation by the humidified scattering-dominant aerosol particles. The increase of JNO2 due to the aerosol hygroscopic growth above the upper boundary layer may affect the tropospheric photochemical processes and this needs to be taken into account in the atmospheric chemical models.
Anterograde delivery of brain‐derived neurotrophic factor to striatum via nigral transduction of recombinant adeno‐associated virus increases neuronal death but promotes neurogenic response following stroke

To explore the role of brain‐derived neurotrophic factor for survival and generation of striatal neurons after stroke, recombinant adeno‐associated viral vectors carrying brain‐derived neurotrophic factor or green fluorescent protein genes were injected into right rat substantia nigra 4–5 weeks prior to 30 min ipsilateral of middle cerebral artery occlusion. The brain‐derived neurotrophic factor–recombinant adeno‐associated viral transduction markedly increased the production of brain‐derived neurotrophic factor protein by nigral cells. Brain‐derived neurotrophic factor was transported anterogradely to the striatum and released in biologically active form, as revealed by the hypertrophic response of striatal neuropeptide Y‐positive interneurons. Animals transduced with brain‐derived neurotrophic factor‐recombinant adeno‐associated virus also exhibited abnormalities in body posture and movements, including tilted body to the right, choreiform movements of left forelimb and head, and spontaneous, so‐called ‘barrel’ rotation along their long axis. The continuous delivery of brain‐derived neurotrophic factor had no effect on the survival of striatal projection neurons after stroke, but exaggerated the loss of cholinergic, and parvalbumin‐ and neuropeptide Y‐positive, γ‐aminobutyric acid‐ergic interneurons. The high brain‐derived neurotrophic factor levels in the animals subjected to stroke also gave rise to an increased number of striatal cells expressing doublecortin, a marker for migrating neuroblasts, and cells double‐labelled with the mitotic marker, 5‐bromo‐2′‐deoxyuridine‐5′monophosphate, and early neuronal (Hu) or striatal neuronal (Meis2) markers. Our findings indicate that long‐term anterograde delivery of high levels of brain‐derived neurotrophic factor increases the vulnerability of striatal interneurons to stroke‐induced damage. Concomitantly, brain‐derived neurotrophic factor potentiates the stroke‐induced neurogenic response, at least at early stages.
Potency of Allium sativum and Allium cepa Oils against Schistosoma mansoni Infection in Mice

Introduction: It has been reported that garlic (Allium sativum) and onion (Allium cepa) are used all over the world in different diseases, such as infections, injuries, gastrointestinal dysfunctions and cardiovascular diseases. Therefore, our aim in this work was to study the ability of garlic and onion oils to offset the infectivity as well as the metabolic disturbances induced by Schistosoma mansoni parasitism. Methods: The two current drugs were given in a dosage of 5ml / kg body weight/ day. Three aspects of drug action were investigated, the effect on S. mansoni infection, the effect on liver functions, and on liver metabolism. The parasitological investigation included worm burden and ova count. Results: Serum biochemical analysis of infected mice revealed a significant increase in the levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT) , γ – glutamyltransferase (GGT) , alkaline phosphatase ( ALP), acid phosphatase (AP), while a decrease in glucose, total lipids total cholesterol, high - and low- density lipoproteins cholesterol (HDL and LDL), triglycerides, total proteins and albumin was observed. Liver tissue analysis of infected animals showed a marked increase in L- hydroxyproline (HP) concentration and xanthine oxidase (XO) activity accompanied with a reduction in total adenosinetriphosphatase (ATPase) and phosphofructokinase (PFK) enzymatic activities. Treatment with either garlic or onion oils greatly normalized liver function enzymes and variably improved the other parameters with a noticeable reduction in worm burden and ova count. Conclusions: It could be concluded that garlic or onion may play a role against the metabolic disturbances caused by S. mansoni infection, owing to an effect which may be induced by improving the immunological host system and their antioxidant activities.
Directed Expected Utility Networks

A variety of statistical graphical models have been defined to represent the conditional independences underlying a random vector of interest. Similarly, many different graphs embedding various types of preferential independences, such as, for example, conditional utility independence and generalized additive independence, have more recently started to appear. In this paper, we define a new graphical model, called a directed expected utility network, whose edges depict both probabilistic and utility conditional independences. These embed a very flexible class of utility models, much larger than those usually conceived in standard influence diagrams. Our graphical representation and various transformations of the original graph into a tree structure are then used to guide fast routines for the computation of a decision problem’s expected utilities. We show that our routines generalize those usually utilized in standard influence diagrams’ evaluations under much more restrictive conditions. We then proceed .
Ontology-driven similarity approaches to supporting gene func- tional assessment

Motivation: Bio-ontologies, such as the Gene Ontology, represent important sources of prior knowledge that may be automatically integrated to support predictive data analysis tasks. The assessment of similarity of gene products provides the basis for the implementation of classification tools and the automated validation of functional associations. This study discusses alternative techniques for measuring ontology-driven similarity of gene products. Relationships between these types of similarity information and key functional properties, such as gene co-expression, are discussed.
Blind estimators for reverberation time and direct-to-reverberant energy ratio using subband speech decomposition

This paper describes algorithms for estimating two important features associated with the reverberation effect on speech signals: the reverberation time and direct-to-reverberant energy ratio. Both methods are referred to as blind algorithms in the sense that they are entirely based on the reverberant signal itself, not depending on the knowledge of the clean original signal. Proposed schemes use subband analysis to generate more and more reliable information, which is post-processed using basic statistical analysis to provide the desired estimate for each particular feature. Modifications on the original estimation algorithms are introduced to cope with lower SNRs. Performance of both algorithms is assessed under the ACE Challenge scope, which included a set of 288 speech signals for training and 4500 signals for final test. Results indicate the effectiveness of both techniques particularly in high-SNR situations.
Design of a Laser-Induced Breakdown Spectroscopy System for On-Line Quality Analysis of Pulverized Coal in Power Plants

It is vitally important for a power plant to determine the chemical composition of coal prior to combustion in order to obtain optimal boiler control. In this work, a fully software-controlled laser-induced breakdown spectroscopy (LIBS) system comprising a LIBS apparatus and sampling equipment has been designed for possible application to power plants for on-line quality analysis of pulverized coal. Special attention was given to the LIBS system, the data processing methods (especially the normalization with Bode Rule/DC Level) and the specific settings (the software-controlled triggering source, high-pressure gas cleaning device, sample-preparation module, sampling module, etc.), which gave the best direct measurement for C, H, Si, Na, Mg, Fe, Al, and Ti with measurement errors less than 10% for pulverized coal. Therefore, the apparatus is accurate enough to be applied to industries for on-line monitoring of pulverized coal. The method of proximate analysis was also introduced and the experimental error of Aad (Ash, ‘ad’ is an abbreviation for ‘air dried’) was shown in the range of 2.29 to 13.47%. The programmable logic controller (PLC) controlled on-line coal sampling equipment, which is designed based upon aerodynamics, and is capable of performing multipoint sampling and sample-preparation operation.