Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Progress in Building Autonomously Creative Systems

Determining conclusively whether a new version of software creatively exceeds a previous version or a third party system is difficult, yet very important for scientific approaches in Computational Creativity research. We argue that software product and process need to be assessed simultaneously in assessing progress, and we introduce a diagrammatic formalism which exposes various timelines of creative acts in the construction and execution of successive versions of artefactgenerating software. The formalism enables estimations of progress or regress from system to system by comparing their diagrams and assessing changes in quality, quantity and variety of creative acts undertaken; audience perception of behaviours; and the quality of artefacts produced. We present a case study in the building of evolutionary art systems, and we use the formalism to highlight various issues in measuring progress in the building of creative systems.
Temporal binding of neural responses for focused attention in biosonar

Big brown bats emit biosonar sounds and perceive their surroundings from the delays of echoes received by the ears. Broadcasts are frequency modulated (FM) and contain two prominent harmonics sweeping from 50 to 25 kHz (FM1) and from 100 to 50 kHz (FM2). Individual frequencies in each broadcast and each echo evoke single-spike auditory responses. Echo delay is encoded by the time elapsed between volleys of responses to broadcasts and volleys of responses to echoes. If echoes have the same spectrum as broadcasts, the volley of neural responses to FM1 and FM2 is internally synchronized for each sound, which leads to sharply focused delay images. Because of amplitude–latency trading, disruption of response synchrony within the volleys occurs if the echoes are lowpass filtered, leading to blurred, defocused delay images. This effect is consistent with the temporal binding hypothesis for perceptual image formation. Bats perform inexplicably well in cluttered surroundings where echoes from off-side objects ought to cause masking. Off-side echoes are lowpass filtered because of the shape of the broadcast beam, and they evoke desynchronized auditory responses. The resulting defocused images of clutter do not mask perception of focused images for targets. Neural response synchronization may select a target to be the focus of attention, while desynchronization may impose inattention on the surroundings by defocusing perception of clutter. The formation of focused biosonar images from synchronized neural responses, and the defocusing that occurs with disruption of synchrony, quantitatively demonstrates how temporal binding may control attention and bring a perceptual object into existence.
Fighting the spam wars: A remailer approach with restrictive aliasing

We present an effective method of eliminating unsolicited electronic mail (so-called spam) and discuss its publicly accessible prototype implementation. A subscriber to our system is able to obtain an unlimited number of aliases of his/her permanent (protected) E-Mail address to be handed out to parties willing to communicate with the subscriber. It is also possible to set up publishable aliases, which can be used by human correspondents to contact the subscriber, while being useless to harvesting robots and spammers. The validity of an alias can be easily restricted to a specific duration in time, a specific number of received messages, a specific population of senders, and/or in other ways. The system is fully compatible with the existing E-Mail infrastructure and can be immediately accessed via any standard E-Mail client software (MUA). It can be easily deployed at any institution or organization running its private E-Mail server (MTA) with a trivial modification to that server. Our system offers a simple method to salvage the existing population of E-Mail addresses while eliminating all spam aimed at them.
Nondeterministic NC1 Computation

We define the counting classes #NC1, GapNC1, PNC1 and C=NC1. We prove that boolean circuits, algebraic circuits, programs over nondeterministic finite automata, and programs over constant integer matrices yield equivalent definitions of the latter three classes. We investigate closure properties. We observe that #NC1 subseteq #L and that C=NC1 subseteq L. Then we exploit our finite automaton model and extend the padding techniques used to investigate leaf languages. Finally, we draw some consequences from the resulting body of leaf language characterizations of complexity classes, including the unconditional separation of ACC0 from ModPH as well as that of TC0 from the counting hierarchy. Moreover we obtain that dlogtime-uniformity and logspace-uniformity for AC0 coincide if and only if the polynomial time hierarchy equals PSPACE.
A Component-Based FPGA Design Framework for Neuronal Ion Channel Dynamics Simulations

Neuron-machine interfaces such as dynamic clamp and brain-implantable neuroprosthetic devices require real-time simulations of neuronal ion channel dynamics. Field-programmable gate array (FPGA) has emerged as a high-speed digital platform ideal for such application-specific computations. We propose an efficient and flexible component-based FPGA design framework for neuronal ion channel dynamics simulations, which overcomes certain limitations of the recently proposed memory-based approach. A parallel processing strategy is used to minimize computational delay, and a hardware-efficient factoring approach for calculating exponential and division functions in neuronal ion channel models is used to conserve resource consumption. Performances of the various FPGA design approaches are compared theoretically and experimentally in corresponding implementations of the alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) and N-methyl-D-aspartate (NMDA) synaptic ion channel models. Our results suggest that the component-based design framework provides a more memory economic solution, as well as more efficient logic utilization for large word lengths, whereas the memory-based approach may be suitable for time-critical applications where a higher throughput rate is desired
SIMPLIFIED, PHYSICALLY-INFORMED MODELS OF DISTORTION ANDOVERDRIVE GUITAR EFFECTS PEDALS

This paper explores a computationally efficient, physicall y informed approach to design algorithms for emulating guitar distortion circuits. Two iconic effects pedals are studied: the “D istortion” pedal and the “Tube Screamer” or “Overdrive” pedal. The primary distortion mechanism in both pedals is a diode clipper with an embedded low-pass filter, and is shown to follow a nonlinear ordinary differential equation whose solution is co mputationally expensive for real-time use. In the proposed method, a simplified model, comprising the cascade of a conditioning fi lter, memoryless nonlinearity and equalization filter, is chosen for its computationally efficient, numerically robust properties . Often, the design of distortion algorithms involves tuning the par ameters of this filter-distortion-filter model by ear to match the sou nd of a prototype circuit. Here, the filter transfer functions and memoryless nonlinearities are derived by analysis of the protot ype circuit. Comparisons of the resulting algorithms to actual pedals show good agreement and demonstrate that the efficient algor ithms presented reproduce the general character of the modeled pedals.
Potent P2Y12 receptor inhibitors in patients with acute coronary syndrome

Summary Blood platelets are highly activated in the setting of an acute coronary syndrome (ACS). This fact mandates the need for potent platelet inhibition in ACS patients and especially in patients undergoing a percutaneous coronary intervention (PCI). The 2nd generation thienopyridine clopidogrel has been the standard of treatment in the past. Due to its pharmacological properties including a delayed onset of action, a large response variability and an insufficient antiplatelet action in some patients (low responsiveness or high on-treatment platelet reactivity), there was a need to develop, to study and to introduce more potent agents with a fast, reliable and potent antiplatelet action. With the 3rd generation thienopyridine prasugrel and with ticagrelor two potent agents for antiplatelet treatment of ACS patients are available now. Both drugs have demonstrated their superiority compared to clopidogrel in terms of thrombotic risk reduction in large-scale randomized trials. However, for these agents and in line with the expectations towards a more potent anti platelet treatment regimen, a higher risk for bleeding was observed for prasugrel and ticagrelor. Further on, the new anti platelet agents have their own and characteristic contraindications and numerous issues to be considered in clinical practice. This review aims to provide an overview on the state of the art P2Y12 receptor directed inhibition in ACS patients with a focus on patients undergoing a coronary stenting procedure.
Structured Connectivity Augmentation

We initiate the algorithmic study of the following "structured augmentation" question: is it possible to increase the connectivity of a given graph G by superposing it with another given graph H? More precisely, graph F is the superposition of G and H with respect to injective mapping \phi:V(H)->V(G) if every edge uv of F is either an edge of G, or \phi^{-1}(u)\phi^{-1}(v) is an edge of H. Thus F contains both G and H as subgraphs, and the edge set of F is the union of the edge sets of G and \phi(H). We consider the following optimization problem. Given graphs G, H, and a weight function \omega assigning non-negative weights to pairs of vertices of V(G), the task is to find \phi of minimum weight \omega(\phi)=\sum_{xy\in E(H)}\omega(\phi(x)\phi(y)) such that the edge connectivity of the superposition F of G and H with respect to \phi is higher than the edge connectivity of G. Our main result is the following ``dichotomy'' complexity classification. We say that a class of graphs C has bounded vertex-cover number, if there is a constant t depending on C only such that the vertex-cover number of every graph from C does not exceed t. We show that for every class of graphs C with bounded vertex-cover number, the problems of superposing into a connected graph F and to 2-edge connected graph F, are solvable in polynomial time when H\in C. On the other hand, for any hereditary class C with unbounded vertex-cover number, both problems are NP-hard when H\in C. For the unweighted variants of structured augmentation problems, i.e. the problems where the task is to identify whether there is a superposition of graphs of required connectivity, we provide necessary and sufficient combinatorial conditions on the existence of such superpositions. These conditions imply polynomial time algorithms solving the unweighted variants of the problems.
Dynamic Cerebral Autoregulation in Acute Ischemic Stroke Assessed From Spontaneous Blood Pressure Fluctuations

Background and Purpose— This study investigates dynamic cerebral autoregulation assessed from spontaneous blood pressure (ABP) and cerebral blood flow velocity (CBFV) fluctuations and its time course in acute ischemic stroke. Methods— Forty patients admitted with acute ischemic stroke in the territory of the middle cerebral artery (MCA) were enrolled. Admission National Institutes of Health Stroke score was 6±4. Study 1 was performed within 22 (±11) hours and study 2 was performed within 134 (±25) hours of ictus. The final analysis comprised 33 and 29 patients for study 1 and study 2, respectively. Twenty-five age- and sex-matched controls were studied. ABP (Finapres method) and CBFV in both MCAs (transcranial Doppler) were recorded over 10 minutes. Correlations between diastolic and mean ABP and CBFV fluctuations were averaged, yielding the correlation coefficient indices (Dx, Mx). Transfer function analysis was applied to obtain phase shift and gain between ABP and CBFV oscillations. Results— No disturbance of autoregulation was indicated by all parameters at study 1. Separate analyses for clinical severity, stroke side, and size did not reveal significant differences for the various autoregulatory indices at study 1 and 2. At study 2, MCA flow velocity was significantly increased on both sides, the autoregulation index Mx was slightly but significantly (P<0.05) worse on both sides in comparison to study 1, and phase showed a trend toward poorer values on affected sides. No significant differences to controls occurred. Clinical outcome in patients completing both studies was good in all but one patient. Conclusions— Dynamic cerebral autoregulation assessed from spontaneous blood pressure fluctuations does not seem to be relevantly disturbed in early minor MCA stroke. At the subacute stage, slight autoregulatory disturbance may be present.
Towards Spanish Verbs' Selectional Preferences Automatic Acquisition: Semantic Annotation of the SenSem Corpus

We present the results of an agreement task carried out in the framework of the KNOW Project and consisting in manually annotating an agreement sample totaling 50 sentences extracted from the SenSem corpus. Diambiguation was carried out for all nouns, proper nouns and adjectives in the sample, all of which were assigned EuroWordNet (EWN) synsets. As a result of the task, Spanish WN has been shown to exhibit 1) lack of explanatory clarity (it does not define word meanings, but glosses and examplifies them instead; it does not systematically encode metaphoric meanings, either); 2) structural inadequacy (some words appear as hyponyms of another sense of the same word; sometimes there even coexist in Spanish WN a general sense and a specific one related to the same concept, but with no structural link in between; hyperonymy relationships have been detected that are likely to raise doubts to human annotators; there can even be found cases of auto-hyponymy); 3) cross-linguistic inconsistency (there exist in English EWN concepts whose lexical equivalent is missing in Spanish WN; glosses in one language more often than not contradict or diverge from glosses in another language).
Supplementary Material (esi) for Lab on a Chip Eletronic Supplementary Information for B823541d: Fluidic Conduits for Highly Efficient Purification of Target Species in Ewod-driven Droplet Microfluidics 1. Sample Purification by Serial Dilution

In many biochemical assays, the purity of the target species (" TS ") (e.g. specific cells, proteins, DNA, either by themselves or bound to beads) at certain steps is vital for their effectiveness. Concentration/separation of the TS from the non-target species (" nonTS ") becomes critical in such assays. Unlike continuous microfluidics, where the TS is immobilized while wash-buffer is flowed through the channels to remove impurities (i.e. nonTS) 1 , purification in droplet microfluidics (e.g. by EWOD) typically involves serial (i.e., repeated steps of) dilution of the nonTS 2,3 , schematicaly described in Fig. S1. In each wash step, a buffer droplet is added to the sample (Fig. S1(1a)). The TS is actively collected in one region of this combined (" parent ") droplet using one or more differentiating properties, such as magnetic, electric, optical or dimensional 4,5 (Fig. S1(1b)). The droplet is then split so that most of the TS are collected in one of the daughter droplets – " collected " droplet (left) in which TS is concentrated and " depleted " droplet (right) from which TS have been depleted (Fig. S1(1c-1d)). To purify and concentrate TS, not only TS should be concentrated but also nonTS should be depleted from the collected droplet. The distribution of the nonTS between the two daughter droplets, on the other hand, is not actively controllable. It is governed by their initial distribution in the parent droplet and non-specific phenomena such as diffusion and fluidic movement that occur during the purification step. If the nonTS were uniformly distributed in the parent droplet, they would be distributed between the daughter droplets roughly in proportion to their volumes. Thus, even though many nonTS from the parent droplet will be removed in the form of the depleted droplet, the process would still leave a significant proportion of nonTS in the collected droplet. In order to improve the TS purity, therefore, collecting the TS across the incoming buffer droplet has been shown to be helpful 6 , which is initially free from the nonTS (Fig. S1(1a-1b)). The droplet is then stretched (Fig. S1(1c)) and split (Fig. S1(1d)) into the collected and depleted droplets. Even though the original distribution of nonTS in the parent droplet is made favorable for high purity by quickly pulling TS towards the buffer side of the droplet (Fig. S1(1b)), the non-specific transport and redistribution of the nonTS during the subsequent steps (Fig. …
An efficient solution for multi-label classification problem using apriori algorithm(MLC-A)

Recently, multi-label classification has gained prime importance among the classification problems. The applications of classification problems has increased so rapidly that the need for efficient and accurate classifiers has become a vital requirement in the area of data mining. Multi-label classification problem is distinguished from the single label classification because of the capability to handle multiple labels. In this paper, we put forward a good method to predict the multiple labels of an unlabeled instance by using apriori algorithm. The proposed solution MLC-A is able to find unknown labels for any test instance by checking for the presence of particular set of attributes, along with their discretized values. MLC-A intends to employ Apriori algorithm for multi-label classification purpose, in contrast, to the well known existing methods. Apriori algorithm is utilized to find the relationship between attributes and labels by generating rules. The generated rules will find the occurrence of a label given the existence of various attributes. The experimental results on datasets of yeast, scene and emotions had given excellent accuracy. Using MLC-A the time complexity has reduced to a great extend. The accuracy and efficiency of the proposed method is evaluated by using hamming loss and is compared to the state of art.
- 1-Programmer-Friendly Refactoring Tools

Tools that perform semi-automated refactoring are currently under-utilized by programmers. If more programmers adopted refactoring tools, software projects could make enormous productivity gains. However, as more advanced refactoring tools are designed, a great chasm widens between how the tools must be used and how programmers want to use them. The proposed research will bridge this chasm by exposing usability guidelines that will direct the design of the next generation of programmer-friendly refactoring tools, so that refactoring tools fit the way programmers behave, not vice-versa.
The Case for a Distributed Solar Dynamo Shaped by Near-Surface Shear

Arguments for and against the widely accepted picture of a solar dynamo being seated in the tachocline are reviewed, and alternative ideas concerning dynamos operating in the bulk of the convection zone, or perhaps even in the near-surface shear layer, are discussed. Based on the angular velocities of magnetic tracers, it is argued that the observations are compatible with a distributed dynamo that may be strongly shaped by the near-surface shear layer. Direct simulations of dynamo action in a slab with turbulence and shear are presented to discuss filling factor and tilt angles of bipolar regions in such a model.
A User-based Approach to Multiway Polarity Classification

Sentiment analysis deals with inferring people’s sentiments and opinions from texts. An important aspect of sentiment analysis is polarity classification, which consists of inferring a document’s polarity – the overall sentiment conveyed by the text – in the form of a numerical rating. In contrast to existing approaches to polarity classification, we propose to take the authors of the documents into account. Specifically, we present a nearest-neighbour collaborative approach that utilises novel models of user similarity. Our evaluation shows that our approach improves on state-of-the-art performance in terms of classification error and runtime, and yields insights regarding datasets for which such an improvement is achievable.
Reorganization and plastic changes of the human brain associated with skill learning and expertise

Novel experience and learning new skills are known as modulators of brain function. Advances in non-invasive brain imaging have provided new insight into structural and functional reorganization associated with skill learning and expertise. Especially, significant imaging evidences come from the domains of sports and music. Data from in vivo imaging studies in sports and music have provided vital information on plausible neural substrates contributing to brain reorganization underlying skill acquisition in humans. This mini review will attempt to take a narrow snapshot of imaging findings demonstrating functional and structural plasticity that mediate skill learning and expertise while identifying converging areas of interest and possible avenues for future research.
A Recent Reversal in the Poleward Shift of Western North Pacific Tropical Cyclones

Recent studies have revealed a global, poleward migration trend of tropical cyclones (TCs) in terms of annual‐averaged latitude of lifetime maximum intensity under the global warming. The TCs in the western North Pacific (WNP) make the largest contribution to this trend. One existing hypothesis is that there is a linkage between poleward migration of TCs and anthropogenic forcing. Here we introduce a new measurement, the lifetime‐averaged latitude weighted by TC destructive potential, to detect the meridional migration of the WNP TCs, which is more reliable and meaningful as it considers not only past data uncertainty but also public concerns. Our results show that the trend of WNP TC migration reversed during the recent warming slowing‐down period (after ~1999). Different from the existing hypothesis, it is the change of regional pattern of sea surface temperature that contributes greatly to the meridional migration of WNP TCs.
Energy Disaggregation via Learning Powerlets and Sparse Coding

In this paper, we consider the problem of energy disaggregation, i.e., decomposing a whole home electricity signal into its component appliances. We propose a new supervised algorithm, which in the learning stage, automatically extracts signature consumption patterns of each device by modeling the device as a mixture of dynamical systems. In order to extract signature consumption patterns of a device corresponding to its different modes of operation, we define appropriate dissimilarities between energy snippets of the device and use them in a subset selection scheme, which we generalize to deal with time-series data. We then form a dictionary that consists of extracted power signatures across all devices. We cast the disaggregation problem as an optimization over a representation in the learned dictionary and incorporate several novel priors such as device-sparsity, knowledge about devices that do or do not work together as well as temporal consistency of the disaggregated solution. Real experiments on a publicly available energy dataset demonstrate that our proposed algorithm achieves promising results for energy disaggregation.