Miracle-dz/UniFAR-FTUs huggingface dataset:
A Flexible Semantic Framework for Effects

Effects are a powerful and convenient component of programming. They enable programmers to interact with the user, take advantage of efficient stateful memory, throw exceptions, and non-deterministically execute programs in parallel. However, they also complicate every aspect of reasoning about a program or language, and as a result it is crucially important to have a good understanding of what effects are and how they work. In this paper we present a new framework for formalizing the semantics of effects that is more general and thorough than previous techniques while clarifying many of the important concepts. By returning to the category-theoretic roots of monads, our framework is rich enough to describe the semantics of effects for a large class of languages including common imperative and functional languages. It is also capable of capturing more expressive, precise, and practical effect systems than previous approaches. Finally, our framework enables one to reason about effects abstractly, and so can be applied to many stages of language design and implementation in order to create more broadly applicable tools for programming languages.
3D inkjet printed radio frequency inductors and capacitors

Inkjet printing has emerged as an ideal method for the fabrication of low cost and efficient electronic systems. However, most of the printed designs at present utilize 2D inkjet printing of metallic inks on conventional substrates. In order to have fully printed RF components, the substrate must also be printed. 3D printing of polymers can be an ideal mechanism for printing substrates, however typically such materials cannot handle high sintering temperatures (>150 0C) required for nanoparticles based metallic inks. In this work, an all-inkjet printed process is demonstrated that utilizes 3D inkjet printing of a UV-cured dielectric material in combination with the printing of a particle free conductive silver organo-complex (SOC) ink for realization of inductors and capacitors. The processing temperature does not exceed 80 0C and still state of the art conductivity of 1×107 S/m is achieved. Both the conductive ink and dielectric have roughness values under 500 nm. The inductor and capacitor exhibit quality factors of 8 and 20 respectively in the high MHz and GHz regime.
Select Figures and Text Excerpts from Epilepsy Across the Spectrum: Promoting Health and Understanding

The Institute of Medicine (IOM) examined the public health dimensions of the epilepsies with a focus on four areas: (1) public health surveillance and data collection and integration; (2) population and public health research; (3) health policy, health care, and human services; and (4) education for providers, people with epilepsy and their families, and the public. In the resulting report, Epilepsy Across the Spectrum: Promoting Health and Understanding, the committee describes its vision for achieving a better understanding of the public health dimensions of the epilepsies and for promoting health and understanding.
A Framework for Active Distributed

Dynamically evolving a widely distributed service or application is a challenging systems design task. In this paper, we describe a plausible, high-level design for a common software framework that supports such extensible distributed services. Our design requires that the distributed service be implemented in an interpreted language, but our framework allows transparent and on-demand procedure instantiation at agents of the distributed service. In addition, this framework enables distributed services to be composed from re-usable modules, and service sessions to be initiated from a single site.
The control of semi-autonomous two-wheeled robots undergoing large payload-variations

We report on the control of semi-autonomous two-wheeled mobile robots undergoing large variations of the payload. These robots being underactuated, their control poses some challenges when resorting to a simple controller. The latter being a linear controller, its robustness with respect to model uncertainty needs to be investigated. To do this, we conducted a time-domain analysis of robustness of the foregoing controller with respect to parametric and unmodeled dynamics uncertainty. The controller, which is designed by a dominant second-order pole technique, turns out to be fragile (as opposed to robust) with respect to unmodeled dynamics uncertainty. In order to cope with this problem, a linear-quadratic regulator is designed. By numerical simulation we show that the latter features robustness with respect to both types of uncertainty.
Surrogate markers for cardiovascular disease: structural markers.

Pignoli et al1 validated the concept that intima-media thickness (IMT), as measured by B-mode ultrasound and applied either in vitro or in situ at the time of autopsy, reflected direct measurements of aortic and/or carotid specimens. Values obtained by ultrasound at autopsy and by direct measurement were similar to those obtained from living subjects. The characteristic double-line pattern was most consistently found in the far wall of postmortem specimens judged to be relatively normal or affected only by fatty streaks. Histologically, these segments showed homogeneous intima with varying amounts of intimal thickening, intimal fibrosis, internal elastic lamina fragmentation, and duplication. In specimens with more advanced atherosclerosis, the double-line pattern was sometimes perturbed and more complex; these samples showed evidence of a fibrous/muscular cap with a lipid and/or necrotic core and, histologically, the intima showed focal areas of fibrotic smooth muscle cell proliferation, microcalcification, and necrosis. Based on this important article, it is clear that carotid IMT is a direct measure of the status of the vascular wall, and abnormalities are not a surrogate but a direct measure of atherosclerotic and arteriosclerotic processes. The issue of surrogacy pertains to whether a measurement in the carotid bed is associated with atherosclerosis in other beds, particularly the coronary bed and, even more important, whether this measurement is predictive of vascular events that result from atherothrombotic disease. ### Methodology Carotid ultrasound is routinely applied for evaluation of ischemic cerebrovascular signs (eg, bruits) and symptoms. In the context of risk stratification, however, the goal is to identify preclinical disease. The degree of carotid disease that appears to be of prognostic value is much subtler, requiring meticulous and detailed measurements of IMT through B-mode ultrasound. These measurements can be made in a reproducible and reliable fashion if sonographers and those making the measurements are trained comprehensively and …
KELT-6b: A P ∼ 7.9 DAY HOT SATURN TRANSITING A METAL-POOR STAR WITH A LONG-PERIOD COMPANION

We report the discovery of KELT-6b, a mildly inflated Saturn-mass planet transiting a metal-poor host. The initial transit signal was identified in KELT-North survey data, and the planetary nature of the occulter was established using a combination of follow-up photometry, high-resolution imaging, high-resolution spectroscopy, and precise radial velocity measurements. The fiducial model from a global analysis including constraints from isochrones indicates that the V = 10.38 host star (BD+31 2447) is a mildly evolved, late-F star with Teff = 6102 ± 43 K, , and [Fe/H] = −0.28 ± 0.04, with an inferred mass M⋆ = 1.09 ± 0.04 M☉ and radius . The planetary companion has mass MP = 0.43 ± 0.05 MJup, radius , surface gravity , and density . The planet is on an orbit with semimajor axis a = 0.079 ± 0.001 AU and eccentricity , which is roughly consistent with circular, and has ephemeris of Tc(BJDTDB) = 2456347.79679 ± 0.00036 and P = 7.845631 ± 0.000046 days. Equally plausible fits that employ empirical constraints on the host-star parameters rather than isochrones yield a larger planet mass and radius by ∼4}–7}. KELT-6b has surface gravity and incident flux similar to HD 209458b, but orbits a host that is more metal poor than HD 209458 by ∼0.3 dex. Thus, the KELT-6 system offers an opportunity to perform a comparative measurement of two similar planets in similar environments around stars of very different metallicities. The precise radial velocity data also reveal an acceleration indicative of a longer-period third body in the system, although the companion is not detected in Keck adaptive optics images.
Water Surface Modeling from a Single Viewpoint Video

We introduce a video-based approach for producing water surface models. Recent advances in this field output high-quality results but require dedicated capturing devices and only work in limited conditions. In contrast, our method achieves a good tradeoff between the visual quality and the production cost: It automatically produces a visually plausible animation using a single viewpoint video as the input. Our approach is based on two discoveries: first, shape from shading (SFS) is adequate to capture the appearance and dynamic behavior of the example water; second, shallow water model can be used to estimate a velocity field that produces complex surface dynamics. We will provide qualitative evaluation of our method and demonstrate its good performance across a wide range of scenes.
Dopamine-Mediated Reinforcement Learning Signals in the Striatum and Ventromedial Prefrontal Cortex Underlie Value-Based Choices

A large body of evidence exists on the role of dopamine in reinforcement learning. Less is known about how dopamine shapes the relative impact of positive and negative outcomes to guide value-based choices. We combined administration of the dopamine D2 receptor antagonist amisulpride with functional magnetic resonance imaging in healthy human volunteers. Amisulpride did not affect initial reinforcement learning. However, in a later transfer phase that involved novel choice situations requiring decisions between two symbols based on their previously learned values, amisulpride improved participants' ability to select the better of two highly rewarding options, while it had no effect on choices between two very poor options. During the learning phase, activity in the striatum encoded a reward prediction error. In the transfer phase, in the absence of any outcome, ventromedial prefrontal cortex (vmPFC) continually tracked the learned value of the available options on each trial. Both striatal prediction error coding and tracking of learned value in the vmPFC were predictive of subjects' choice performance in the transfer phase, and both were enhanced under amisulpride. These findings show that dopamine-dependent mechanisms enhance reinforcement learning signals in the striatum and sharpen representations of associative values in prefrontal cortex that are used to guide reinforcement-based decisions.
Transition Hough forest for trajectory-based action recognition

In this paper, we propose a new discriminative framework based on Hough forests that enables us to efficiently recognize and localize sequential data in the form of spatio-temporal trajectories. Contrary to traditional decision forest-based methods where predictions are made independently of its output temporal context, we introduce the concept of "transition", which enforces the temporal coherence of estimations and further enhances the discrimination between action classes. We start applying our proposed framework to the problem of recognizing and localizing fingertip written trajectories in mid-air using an egocentric camera. To this purpose, we present a new challenging dataset that allows us to evaluate and compare our method with previous approaches. Finally, we apply our framework to general human action recognition using local spatio-temporal trajectories obtaining comparable to state-of-the-art performance on a public benchmark.
D1/D5 Dopamine Receptor Activation Increases the Magnitude of Early Long-Term Potentiation at CA1 Hippocampal Synapses

The role of the mesolimbic dopaminergic system in the reinforcement of learning suggests that dopamine should be able to modulate activity-dependent synaptic plasticity. We have examined the effect of D1/D5 agonists on early long-term potentiation (LTP) (40 min) in the CA1 region of hippocampal slices. D1/D5 agonists (+)bromo-APB, 6-chloro-PB, and dihydrexidine increased the magnitude of LTP in a synapse-specific manner (by ∼10, 15, and 20%, respectively). This D1/D5 effect was mimicked by a low dose (10 μm) of the adenylyl cyclase activator forskolin. The D1/D5 antagonist (+)SCH 23390 reduced early LTP. In catecholamine-depleted slices, LTP was smaller by ∼20-25% and could not be decreased further by D1/D5 antagonist. Under these conditions, D1/D5 agonist 6-chloro-PB and forskolin produced a larger enhancement of LTP (20–25%), restoring it to the control level. At the same dose, dideoxyforskolin did not affect early LTP. The D1/D5 agonist effect was completely blocked by the D1/D5 antagonist (+)SCH 23390. These results indicate that dopamine produces a synapse-specific enhancement of early LTP through D1/D5 receptors and cAMP.
Dynamic pressure maps for wings and tails of pigeons in slow, flapping flight, and their energetic implications

SUMMARY Differential pressure measurements offer a new approach for studying the aerodynamics of bird flight. Measurements from differential pressure sensors are combined to form a dynamic pressure map for eight sites along and across the wings, and for two sites across the tail, of pigeons flying between two perches. The confounding influence of acceleration on the pressure signals is shown to be small for both wings and tail. The mean differential pressure for the tail during steady, level flight was 25.6 Pa, which, given an angle of attack for the tail of 47.6°, suggests the tail contributes 7.91% of the force required for weight support, and requires a muscle-mass specific power of 19.3 W kg-1 for flight to overcome its drag at 4.46 m s-1. Differential pressures during downstroke increase along the wing length, to 300-400 Pa during take-off and landing for distal sites. Taking the signals obtained from five sensors sited along the wing at feather bases as representative of the mean pressure for five spanwise elements at each point in time, and assuming aerodynamic forces act within the x-z plane (i.e. no forces in the direction of travel) and perpendicular to the wing during downstroke, we calculate that 74.5% of the force required to support weight was provided by the wings, and that the aerodynamic muscle-mass specific power required to flap the wings was 272.7 W kg-1.
Adaptive and Self-adaptive Evolutionary Computations

This paper reviews the various studies that have introduced adaptive and self-adaptive parameters into Evolutionary Computations. A formal definition of an adaptive evolutionary computation is provided with an analysis of the types of adaptive and self-adaptive parameter update rules currently in use. Previous studies are reviewed and placed into a categorization that helps to illustrate their similarities and differences.
Deep, super-narrow neural network is a universal classifier

Deep architecture models are known to be conducive to good generalisation for certain types of classification tasks. Existing unsupervised and semi-supervised training methods do not explain why and when deep internal representations will be effective. We investigate the fundamental principles of representation in deep architectures by devising a method for binary classification in multi-layer feed forward networks with limited breadth. We show that, given enough layers, a super-narrow neural network, with two neurons per layer, is capable of shattering any separable binary dataset. We also show that datasets that exhibit certain type of symmetries are better suited for deep representation and may require only few hidden layers to produce desired classification.
A new non-polynomial solution to multivariate Hermite-Birkhoff interpolation

A new solution to the multivariate Hermite-Birkhoff interpolation problem is presented. The classical approach to this problem consists in constructing the minimum degree polynomial, which coincides with the prescribed function and derivative values at the sample points. Here the interpolant is represented as a truncated Multipoint Taylor (MT) series. A MT series can be regarded as an extension to multiple points of the ordinary (one point) Taylor series. The constructed MT series converges when (i) the number of derivatives tends to infinity, while the number of sample points remains finite, or (ii) when the spacing between sample points tends to zero, while the number of derivatives remains finite. The MT series region of convergence depends on the support of its basis functions and the location of the singularities of the function represented. Examples are given of the construction of interpolants in one and two dimensions and for different samples grid types. A comparison between the numerical results achieved with this new method and those obtained with onedimensional polynomial Hermite-Birkhoff interpolation is made. Our interpolant does not suffer from the ill conditioning seen with the classical polynomial solution for certain data configurations. It is always numerically stable in its region of convergence. In addition, it is computationally much more efficient than the polynomial approach, because no basis function construction phase is required. Finally, the presented construction is applicable to interpolation in any number of dimensions and could also be regarded as a finite element data representation, which uses both functional values as well as derivative values.
The Analgesic Effect of the Mitochondria-Targeted Antioxidant SkQ1 in Pancreatic Inflammation

Background. Chronic pancreatitis is one of the main risk factors for pancreatic cancer. In acute and chronic pancreatitis, oxidative stress is thought to play a key role. In this respect, the recently described mitochondria-targeted antioxidant SkQ1 effectively scavenges reactive oxygen species at nanomolar concentrations. Therefore, we aimed to characterize the influence of SkQ1 on tissue injury and pain in acute and chronic pancreatitis. Methods. Both acute and chronic pancreatitis were induced in C57BL/6 mice by intraperitoneal cerulein injections and treatment with SkQ1 was carried out by peroral applications. Hyperalgesia was assessed by behavioral observation and measurement of abdominal mechanical sensitivity. Blood serum and pancreatic tissue were harvested for analysis of lipase and histology. Results. SkQ1 did not influence pain, serological, or histological parameters of tissue injury in acute pancreatitis. In chronic pancreatitis, a highly significant reduction of pain-related behavior (p < 0.0001) was evident, but histological grading revealed increased tissue injury in SkQ1-treated animals (p = 0.03). Conclusion. After SkQ1 treatment, tissue injury is not ameliorated in acute pancreatitis and increased in chronic pancreatitis. However, we show an analgesic effect in chronic pancreatitis. Further studies will need to elucidate the risks and benefits of mitochondria-targeted antioxidants as an analgesic.
Can the Use of Neuromuscular Electrical Stimulation Be Improved to Optimize Quadriceps Strengthening?

Context: Neuromuscular electrical stimulation (NMES) is a common modality used to retrain muscles and improve muscular strength after injury or surgery, particularly for the quadriceps muscle. There are parameter adjustments that can be made to maximize the effectiveness of NMES. While NMES is often used in clinical practice, there are some limitations that clinicians should be aware of, including patient discomfort, muscle fatigue, and muscle damage. Evidence Acquisition: PubMed was searched through August 2014 and all articles cross-referenced. Study Design: Clinical review. Level of Evidence: Level 3. Results: Clinicians can optimize torque production and decrease discomfort by altering parameter selection (pulse duration, pulse frequency, duty cycle, and amplitude). Pulse duration of 400 to 600 µs and a pulse frequency of 30 to 50 Hz appear to be the most effective parameters to optimize torque output while minimizing discomfort, muscle fatigue, or muscle damage. Optimal electrode placement, conditioning programs, and stimulus pattern modulation during long-term NMES use may improve results. Conclusion: Torque production can be enhanced while decreasing patient discomfort and minimizing fatigue.
Using hierarchical clustering for learning theontologies used in recommendation systems

Ontologies are being successfully used to overcome semanticheterogeneity, and are becoming fundamental elements of the SemanticWeb. Recently, it has also been shown that ontologies can be used tobuild more accurate and more personalized recommendation systems byinferencing missing user's preferences. However, these systemsassume the existence of ontologies, without considering theirconstruction. With product catalogs changing continuously, newtechniques are required in order to build these ontologies in realtime, and autonomously from any expert intervention.This paper focuses on this problem and show that it is possible tolearn ontologies autonomously by using clustering algorithms. Results on the MovieLens and Jester data sets show that recommendersystem with learnt ontologies significantly outperform the classical recommendation approach.
Reducing power in high-performance microprocessors

Power consumption has become one of the biggest challenges in high-performance microprocessor design. The rapid increase in the complexity and speed of each new CPU generation is outstripping the benefits of voltage reduction and feature size scaling. Designers are thus continuously challenged to come up with innovative ways to reduce power, while trying to meet all the other constraints imposed on the design. This paper presents an overview of the issues related to power consumption in the context of Intel CPUs. The main trends that are driving the increased focus on design for low power are described. System and benchmarking issues, and sources of power consumption in a high-performance CPU are briefly described. Techniques that have been tried on real designs in the past are described. The role of CAD tools and their limitations in this domain are also discussed. In addition, areas that need increased research focus in the future are also pointed out.
Simple Ecological Rules Yield Complex Agent Networks

In complex natural systems (such as ecological systems) it is common for those studying the macro-dynamics of systems to aim to describe, as simply as possible, the interactions between individuals occupying different niches in a system and to validate these by studying whether they account for the complex network of relationships observed in the actual system. We explore a similar principle applied to multi-agent systems: we develop interactions among intelligent agents; these interactions produce complex networks of relationships among the entities in the system in a similar fashion in which ecological networks are formed in nature. The study of the topological features displayed by these networks is helpful for determining the stability of the system of software agents and its relation to the complexity of the network itself. An interaction centred approach for coordination and knowledge sharing among artificial agents is adopted for the implementation of the system.