Miracle-dz/UniFAR-FTUs huggingface dataset:
A Priority-Driven Flow Control Mechanism for Real-Time Traffic in Multiprocessor Networks

Real-time applications when mapped to distributed memory multiprocessors produce periodic messages with an associated deadline and priority. Real-time messages may be hard or soft deadline. Real-time extensions to wormhole routing (WR) with multiple virtual channels (VCs) and priority-based physical link arbitration and VC allocation have been proposed in the literature. With a fixed number of VCs/link, a message can face an unbounded priority inversion, rendering the global priority ineffective. In this paper, we propose a new flow control mechanism called Preemptive Pipelined Circuit Switching for Real-Time messages (PPCS-RT) to reduce the priority inversion problem. For the proposed model, with some architectural support, we present an off-line approach to compute delivery guarantees of hard deadline real-time messages. We also perform a comparison of real-time WR and PPCS-RT in terms of performance with soft deadline traffic. The overall miss ratio percentage is over 30 percent higher for WR than PPCS-RT with one VC/link at high traffic loads. Finally, we compare the architectural complexity of a PPCS-RT router and other real-time routers.
Long‐range transport to Europe: Seasonal variations and implications for the European ozone budget

We use a chemical transport model (GEOS-CHEM) to quantify the contribution of long-range transported pollution to the European ozone ({O}_{3}) budget for the year 1997. The model reproduces the main features observed over Europe for {O}_{3}, carbon monoxide and nitrogen dioxides, as well as two events of enhanced {O}_{3} of North American origin over the eastern North Atlantic and over Europe. North American {O}_{3} fluxes into Europe experience a maximum in spring and summer, reflecting the seasonal variation in photochemical activity and in export pathways. In summer, North American {O}_{3} enters Europe at higher altitudes and lower latitudes because of deep convection, and because the flow over the North Atlantic is mostly zonal in that season. The low-level inflow is only important in spring, when loss rates in the boundary layer over the North Atlantic are weaker. Asian O3 arrives mainly via the westerlies, and usually at higher altitudes than North American O3 because of stronger deep convection over Asia. In addition, Asian O3 fluxes are at a maximum in summer during the monsoon period because of enhanced convection over Asia, increased nitrogen oxides sources from lightning and direct transport towards Europe via the monsoon easterlies. Over Europe, total background accounts for 30 ppbv at the surface. North American and Asian O3 contribute substantially to the annual O3 budget over Europe, accounting for 10.9% and 7.7%, respectively,while the European contribution only accounts for 9.4%. We find that in summer, at the surface, O3 decreases over Europe from 1980 to 1997, reflecting the reduction of European O3 precursor emissions. In the free troposphere, this decrease is compensated by the increase in O3 due to increasing Asian emissions. This may explain the lack of trends observed over most of the European region, especially at mountain sites.
Clavicles, interclavicles, gastralia, and sternal ribs in sauropod dinosaurs: new reports from Diplodocidae and their morphological, functional and evolutionary implications

Ossified gastralia, clavicles and sternal ribs are known in a variety of reptilians, including dinosaurs. In sauropods, however, the identity of these bones is controversial. The peculiar shapes of these bones complicate their identification, which led to various differing interpretations in the past. Here we describe different elements from the chest region of diplodocids, found near Shell, Wyoming, USA. Five morphotypes are easily distinguishable: (A) elongated, relatively stout, curved elements with a spatulate and a bifurcate end resemble much the previously reported sauropod clavicles, but might actually represent interclavicles; (B) short, L‐shaped elements, mostly preserved as a symmetrical pair, probably are the real clavicles, as indicated by new findings in diplodocids; (C) slender, rod‐like bones with rugose ends are highly similar to elements identified as sauropod sternal ribs; (D) curved bones with wide, probably medial ends constitute the fourth morphotype, herein interpreted as gastralia; and (E) irregularly shaped elements, often with extended rugosities, are included into the fifth morphotype, tentatively identified as sternal ribs and/or intercostal elements. To our knowledge, the bones previously interpreted as sauropod clavicles were always found as single bones, which sheds doubt on the validity of their identification. Various lines of evidence presented herein suggest they might actually be interclavicles – which are single elements. This would be the first definitive evidence of interclavicles in dinosauromorphs. Previously supposed interclavicles in the early sauropodomorph Massospondylus or the theropods Oviraptor and Velociraptor were later reinterpreted as clavicles or furculae. Independent from their identification, the existence of the reported bones has both phylogenetic and functional significance. Their presence in non‐neosauropod Eusauropoda and Flagellicaudata and probable absence in rebbachisaurs and Titanosauriformes shows a clear character polarity. This implicates that the ossification of these bones can be considered plesiomorphic for Sauropoda. The proposed presence of interclavicles in sauropods may give further support to a recent study, which finds a homology of the avian furcula with the interclavicle to be equally parsimonious to the traditional theory that furcula were formed by the fusion of the clavicles. Functional implications are the stabilizing of the chest region, which coincides with the development of elongated cervical and caudal vertebral columns or the use of the tail as defensive weapon. The loss of ossified chest bones coincides with more widely spaced limbs, and the evolution of a wide‐gauge locomotor style.
Evaluation of Linear Classifiers on Articles Containing Pharmacokinetic Evidence of Drug-Drug Interactions

BACKGROUND Drug-drug interaction (DDI) is a major cause of morbidity and mortality. DDI research includes the study of different aspects of drug interactions, from in vitro pharmacology, which deals with drug interaction mechanisms, to pharmaco-epidemiology, which investigates the effects of DDI on drug efficacy and adverse drug reactions. Biomedical literature mining can aid both kinds of approaches by extracting relevant DDI signals from either the published literature or large clinical databases. However, though drug interaction is an ideal area for translational research, the inclusion of literature mining methodologies in DDI workflows is still very preliminary. One area that can benefit from literature mining is the automatic identification of a large number of potential DDIs, whose pharmacological mechanisms and clinical significance can then be studied via in vitro pharmacology and in populo pharmaco-epidemiology. EXPERIMENTS We implemented a set of classifiers for identifying published articles relevant to experimental pharmacokinetic DDI evidence. These documents are important for identifying causal mechanisms behind putative drug-drug interactions, an important step in the extraction of large numbers of potential DDIs. We evaluate performance of several linear classifiers on PubMed abstracts, under different feature transformation and dimensionality reduction methods. In addition, we investigate the performance benefits of including various publicly-available named entity recognition features, as well as a set of internally-developed pharmacokinetic dictionaries. RESULTS We found that several classifiers performed well in distinguishing relevant and irrelevant abstracts. We found that the combination of unigram and bigram textual features gave better performance than unigram features alone, and also that normalization transforms that adjusted for feature frequency and document length improved classification. For some classifiers, such as linear discriminant analysis (LDA), proper dimensionality reduction had a large impact on performance. Finally, the inclusion of NER features and dictionaries was found not to help classification.
Creatine supplements in patients with idiopathic inflammatory myopathies who are clinically weak after conventional pharmacologic treatment: Six-month, double-blind, randomized, placebo-controlled trial.

OBJECTIVE To test the hypothesis that oral creatine supplements with exercise are more effective than exercise alone in improving muscle function in patients with established dermatomyositis or polymyositis receiving chronic medical therapies who are clinically weak yet stable. METHODS In a 6-month, 2-center, double-blind, randomized controlled trial, patients were randomized to receive oral creatine supplements (8 days, 20 gm/day then 3 gm/day) or placebo. All patients followed a home exercise program. The primary outcome was aggregate functional performance time (AFPT), reflecting the ability to undertake high-intensity exercise. Secondary outcomes included a functional index measuring endurance and muscle bioenergetics on (31)P magnetic resonance spectroscopy ((31)P MRS). Patients were receiving stable immunosuppressive treatment and/or corticosteroids. RESULTS A total of 37 patients with polymyositis or dermatomyositis were randomized (19 to creatine, 18 to placebo); 29 completed 6 months. Intent-to-treat analyses demonstrated that AFPT improved significantly at 6 months with creatine (median decrease 13%, range -32-8%) compared with placebo (median decrease 3%, range -13-16%; P = 0.029 by Mann-Whitney U test). A completer analysis also showed significant benefits from creatine (P = 0.014). The functional index improved significantly with both creatine and placebo (P < 0.05 by paired Wilcoxon's rank sum test), with a significant benefit between groups in the completer analysis only. Phosphocreatine/beta-nucleoside triphosphate ratios using MRS increased significantly in the creatine group (P < 0.05) but not in the control group. No clinically relevant adverse events were associated with creatine. CONCLUSION Oral creatine supplements combined with home exercises improve functional performance without significant adverse effects in patients with polymyositis or dermatomyositis. They appear safe, effective, and inexpensive.
On the Alleged Illusion of Conscious Will

The belief that conscious will is merely “an illusion created by the brain” appears to be gaining in popularity among cognitive neuroscientists. Its main adherents usually refer to the classic, but controversial ‘Libet-experiments’, as the empirical evidence that vindicates this illusion-claim. However, based on recent work that provides other interpretations of the Libet-experiments, we argue that the illusion-claim is not only empirically invalid, but also theoretically incoherent, as it is rooted in a category mistake; namely, the presupposition that neuronal activity causes conscious will. We show that the illusion-claim is based on the behaviorist ‘input-output’ paradigm, and discuss the notions of ‘self-organization’ and ‘self-steering’ to provide an alternative perspective on the causal efficacy of conscious will. In the final sections, a tentative theoretical picture is sketched of conscious will as an instance of self-steered self-organization. We conclude that the subjective experience of conscious will is not a misguided one, but rather that the mechanisms supporting conscious will are considerably more complex than mainstream cognitive neuroscience currently acknowledges.
Using long short-term memory recurrent neural network in land cover classification on Landsat and Cropland data layer time series

ABSTRACT Land cover maps are significant in assisting agricultural decision making. However, the existing workflow of producing land cover maps is very complicated and the result accuracy is ambiguous. This work builds a long short-term memory (LSTM) recurrent neural network (RNN) model to take advantage of the temporal pattern of crops across image time series to improve the accuracy and reduce the complexity. An end-to-end framework is proposed to train and test the model. Landsat scenes are used as Earth observations, and some field-measured data together with CDL (Cropland Data Layer) datasets are used as reference data. The network is thoroughly trained using state-of-the-art techniques of deep learning. Finally, we tested the network on multiple Landsat scenes to produce five-class and all-class land cover maps. The maps are visualized and compared with ground truth, CDL, and the results of SegNet CNN (convolutional neural network). The results show a satisfactory overall accuracy (> 97% for five-class and > 88% for all-class) and validate the feasibility of the proposed method. This study paves a promising way for using LSTM RNN in the classification of remote sensing image time series.
Indentor tests and finite element modeling of bulk muscular tissue in vivo.

The quasi-static response of bulk muscular tissue to indentation was measured on the posterior lower legs of living human subjects. No residual limbs were tested; all subjects had intact lower limbs. For loads up to 7.0 N on an 8.0 mm diameter flat-tipped indentor, the response was repeatable without prior 'preconditioning'. The data at any test location exhibited substantial random scatter, but did not trend up or down with repeated cycles. At these limited loads (< 7.0 N), hysteresis was always evident but was always < or = 10% of the maximum reaction force generated. At these limited loads, stress relaxation, in the time period between 5 and 1200 seconds after indentation, was < 10% (> 90% confidence). At higher load levels (> 12.0 N), greater hysteresis and prolonged stress relaxation were observed, accompanied by minor tissue damage. In order to estimate the composite material stiffness of the tissue, the indentations were modeled using a materially and geometrically nonlinear, large-strain finite element formulation. The resulting composite material stiffness was nonlinear, and could be approximated using the Jamus-Green-Simpson strain energy function; typical values for the coefficients were c10 = 0.0026 MPa, c01 = 0.00064 MPa, and c11 = 0.0057 MPa.
Universality and the renormalisation group

Several functional renormalisation group (RG) equations including Polchinski flows and Exact RG flows are compared from a conceptual point of view and in given truncations. Similarities and differences are highlighted with special emphasis on stability properties. The main observations are worked out at the example of O(N) symmetric scalar field theories where the flows, universal critical exponents and scaling potentials are compared within a derivative expansion. To leading order, it is established that Polchinski flows and ERG flows — despite their inequivalent derivative expansions — have identical universal content, if the ERG flow is amended by an adequate optimisation. The results are also evaluated in the light of stability and minimum sensitivity considerations. Extensions to higher order and further implications are emphasized.
An Integrated Approach for Airline Flight Selection and Timing, Fleet Assignment, and Aircraft Routing

Airline profits critically depend on the nature and efficiency of service they provide, and accrue from a complex planning process involving schedule design, fleet assignment, aircraft routing, and crew scheduling, which are interrelated to each other within the overall system. We propose in this paper a model that integrates certain aspects of the schedule design, fleet assignment, and aircraft-routing processes, while considering flight retiming and demand recapture issues, along with optional legs, itinerary-based demands, and multiple fare classes. Maintenance routing decisions, as well as through-flight opportunities, are additionally incorporated in our model, and we apply the reformulation-linearization technique to reduce its complexity while introducing hierarchical symmetry-breaking constraints, along with other classes of valid inequalities, to enhance its solvability. A Benders' decomposition-based method is designed to handle the resulting large-scale model formulation. Computational results using real data obtained from United Airlines are presented to demonstrate the potential profitability in applying the proposed approach.
The Value of Initial Ionized Calcium as a Predictor of Mortality and Triage Tool in Adult Trauma Patients

Ionized hypocalcemia is a common finding in critically ill patients, but the relationship between ionized hypocalcemia and mortality risk in trauma patients has not been well established. The aim of this study was to assess the usefulness of initial ionized calcium (iCa) in predicting mortality in the trauma population, and evaluate its superiority over the three other triage tools: base deficit, systemic inflammatory response syndrome (SIRS) score, and triage-revised trauma score (t-RTS). A proand retrospective study was performed on 255 consecutive trauma patients admitted to our Emergency Medical Center from January to December, 2005, who underwent arterial blood gas analysis. Multivariate logistic regression analysis confirmed iCa (≤0.88 mM/L), low Glasgow coma scale score, and a large transfusion amount to be significant risk factors associated with mortality (p<0.05). The sensitivities of iCa, base deficit, SIRS score, and t-RTS were 82.9%, 76.4%, 67.1%, and 74.5%, and their specificities were 41.0%, 64.1%, 64.1%, and 87.2%, respectively. Receiver operating characteristic curve analysis determined the areas under the curves of these parameters to be 0.607±0.062, 0.736±0.056, 0.694±0.059, and 0.875 ±0.043, respectively (95% confidence interval). Although initial iCa (≤0.88 mM/L) was confirmed as a significant risk factor associated with mortality, it exhibited a poorer discriminative power for mortality prediction than other predictors, especially t-RTS.
Active learning for interactive machine translation

Translation needs have greatly increased during the last years. In many situations, text to be translated constitutes an unbounded stream of data that grows continually with time. An effective approach to translate text documents is to follow an interactive-predictive paradigm in which both the system is guided by the user and the user is assisted by the system to generate error-free translations. Unfortunately, when processing such unbounded data streams even this approach requires an overwhelming amount of manpower. Is in this scenario where the use of active learning techniques is compelling. In this work, we propose different active learning techniques for interactive machine translation. Results show that for a given translation quality the use of active learning allows us to greatly reduce the human effort required to translate the sentences in the stream.
Stimulus-dependent Maximum Entropy Models of Neural Population Codes

Neural populations encode information about their stimulus in a collective fashion, by joint activity patterns of spiking and silence. A full account of this mapping from stimulus to neural activity is given by the conditional probability distribution over neural codewords given the sensory input. For large populations, direct sampling of these distributions is impossible, and so we must rely on constructing appropriate models. We show here that in a population of 100 retinal ganglion cells in the salamander retina responding to temporal white-noise stimuli, dependencies between cells play an important encoding role. We introduce the stimulus-dependent maximum entropy (SDME) model—a minimal extension of the canonical linear-nonlinear model of a single neuron, to a pairwise-coupled neural population. We find that the SDME model gives a more accurate account of single cell responses and in particular significantly outperforms uncoupled models in reproducing the distributions of population codewords emitted in response to a stimulus. We show how the SDME model, in conjunction with static maximum entropy models of population vocabulary, can be used to estimate information-theoretic quantities like average surprise and information transmission in a neural population.
Learning by doing: an fMRI study of feedback-related brain activations

Extracting meaningful information from the positive and negative outcomes of actions is a key requirement for learning. To define the neural correlates of feedback processing, rapid event-related functional magnetic resonance imaging was used in an associative learning paradigm in normal human volunteers. Positive (compared with negative) feedback was associated with activations in the ventral striatum, midbrain and anterior and posterior cingulate cortex. No activations were seen for the comparison negative >positive feedback. Blood oxygenation level-dependent responses from the midbrain and the anterior cingulate cortex showed a phasic increase in response to positive feedback, whereas a decrease in response was seen for negative feedback. These results underscore the role of the reward system in feedback learning.
Software reuse

Software reuse is the process of creating software systems from existing software rather than building software systems from scratch. This simple yet powerful vision was introduced in 1968. Software reuse has, however, failed to become a standard software engineering practice. In an attempt to understand why, researchers have renewed their interest in software reuse and in the obstacles to implementing it. This paper surveys the different approaches to software reuse found in the research literature. It uses a taxonomy to describe and compare the different approaches and make generalizations about the field of software reuse. The taxonomy characterizes each reuse approach in terms of its reusable artifacts and the way these artifacts are abstracted, selected, specialized, and integrated. Abstraction plays a central role in software reuse. Concise and expressive abstractions are essential if software artifacts are to be effectively reused. The effectiveness of a reuse technique can be evaluated in terms of cognitive distance—an intuitive gauge of the intellectual effort required to use the technique. Cognitive distance is reduced in two ways: (1) Higher level abstractions in a reuse technique reduce the effort required to go from the initial concept of a software system to representations in the reuse technique, and (2) automation reduces the effort required to go from abstractions in a reuse technique to an executable implementation. This survey will help answer the following questions: What is software reuse? Why reuse software? What are the different approaches to reusing software? How effective are the different approaches? What is required to implement a software reuse technology? Why is software reuse difficult? What are the open areas for research in software reuse?