Miracle-dz/UniFAR-FTUs huggingface dataset:
SemEval-2017 Task 7: Detection and Interpretation of English Puns

A pun is a form of wordplay in which a word suggests two or more meanings by exploiting polysemy, homonymy, or phonological similarity to another word, for an intended humorous or rhetorical effect. Though a recurrent and expected feature in many discourse types, puns stymie traditional approaches to computational lexical semantics because they violate their one-sense-per-context assumption. This paper describes the first competitive evaluation for the automatic detection, location, and interpretation of puns. We describe the motivation for these tasks, the evaluation methods, and the manually annotated data set. Finally, we present an overview and discussion of the participating systems’ methodologies, resources, and results.
Paragraph retrieval for why-question answering

In the current research project, we aim at developing a system for answering why-questions (why-QA). In previous research, we investigated the possibilities of answer extraction for why-QA exploiting discourse structure in the source text. One conclusion was that many why-questions require a complete paragraph as an answer. In the present paper, we will first discuss the results and the main conclusions that we obtained from these experiments. Then, we will present our research plans concerning paragraph retrieval for why-QA.
Performance of the RENA-3 IC with position-sensitive CZT and CdTe detectors

The RENA-3 (Readout Electronics for Nuclear Applications) is a 36-channel self-resetting, charge sensitive amplifier/shaper IC with trigger output, wide energy range and sparse readout designed for use with position-sensitive, spectroscopy-grade radiation detectors. It has in recent years been favored to provide the front-end electronics in prototype instruments for various applications — from space physics research through medical imaging to homeland security — that employ CZT or CdTe in the form of planar sensor assemblies or monolithic pixel/strip arrays. We will present a summary of spectroscopic data drawn from the body of RENA-3-based results obtained in our laboratories and by other RENA-3 users. Spectroscopic performance metrics will be discussed relative to the requirements of the specific application targeted in each case as well as from the general standpoint of what may be achievable within this detector-array/RENA-3 approach. A method to automate the test and calibration of RENA-3 ICs will also be described.
Analysing and Predicting Patient Arrival Times in Hospitals using Hidden Markov Models

We fit a Hidden Markov Model (HMM) to patient arrivals data, input as a discrete data trace, collected over many months. The processing of the data trace makes use of a simple binning technique, followed by clustering, before it is input into the Baum-Welch algorithm, which estimates the parameters of the underlying Markov chain’s statetransition matrix. Upon convergence, the HMM is used to predict its own synthetic traces of patient arrivals, behaving as a fluid input model. Utilizing the Viterbi algorithm, one can decode the meaning of the hidden states of the HMM, further understanding the varying rate of patient arrivals at different times of the hospital schedule. The HMM is validated by comparing means, standard deviations and autocorrelation functions of raw and synthetic traces. Finally, an efficient set up is explored to provide optimal parameter initialization for the HMM, including choosing the number of hidden states. We conclude with a summary of our findings, comparing results with other work in the field, and proposals for future work.
An efficient dynamic resource allocation algorithm for downlink MIMO - OFDMA systems

Multiple Input Multiple Output (MIMO) - Orthogonal Frequency Division Multiple Access (OFDMA) systems provide high spectral efficiency due to its integrated space-frequency and multi-user diversity. In this paper a Dynamic Resource Allocation (DRA) scheme has been devised for MIMO - OFDMA systems in a downlink scenario. The scheme optimizes the power distribution and guarantees desired Quality of Service (QoS) to each user. The available channel state information at the Base Station (BS) is utilized in order to help these practical schemes to improve system performance and to satisfy various QoS constraints. Computer simulation results demonstrate the proposed scheme performance with the comparison of previous allocation schemes and the proposed scheme satisfy the proportionality constraints and achieves high system capacity.
Raindrop-Tampered Scene Detection and Traffic Flow Estimation for Nighttime Traffic Surveillance

In this paper, we propose an intelligent highway surveillance system that performs self-diagnosis and detects conditions when the camera is seriously tampered by raindrops at night. The system also provides solutions to analyze the traffic flow under the challenging nighttime raindrop-tampered conditions. To deal with the challenging scenes, we extract effective features via salient region detection and block segmentation. The extracted features are used to train a support vector machine to achieve self-diagnosis. For traffic flow analysis, we use the extracted features in the region of interest and construct a regression model to get an estimated vehicle count for each frame. The vehicle counts in consecutive frames form a vehicle count sequence. We propose a mapping model to acquire the desired per-minute traffic flow from the vehicle count sequence. The model utilizes state transfer likelihoods and takes into account the length of the segmented vehicle count sequence. The experiments on highly challenging data sets have demonstrated that the proposed system can effectively estimate the traffic flow for raindrop-tampered highway surveillance cameras at night.
Domesticating the Democratic Deficit? The Role of National Parliaments and Parties in the EU’s System of Governance

The Lisbon Treaty (LT) grounds the European Union (EU) in the principles of political equality and representative democracy. It also acknowledges the role national parliaments play in realizing these norms within the EU’s system of governance - the first time they have been mentioned in the main body of the Treaty on European Union (TEU) - and introduced the Early Warning Mechanism (EWM) as a means for national parliaments (NPs) to be involved in EU policymaking. This article analyses the normative and empirical connections between political equality and representative democracy at the domestic level, and the ways they are embodied in parliamentary elections between competing parties. It then assesses how far these links continue to operate in the domestic debate of EU affairs before undertaking a first evaluation of the use NPs have made of the Early Warning Mechanism (EWM). We argue that in many respects they have been undermined by the integration process, which has reduced the capacity of national representative institutions to perform the tasks assigned to them by the Treaty.
Retrieving Web Images to Enrich Music Representation

Audiovisual media which integrates visual media with audio to enrich music representation, such as music video (MV) or music slideshow, is now more welcome than only audio. In this paper, we proposed a novel approach to automatically retrieve Web images appropriately suitable to a given music song. In this approach, an imageability measurement is first proposed to select those meaningful words and phrases from lyrics, as queries for further image search. Then, considering the possible ambiguities of queries may cause Web image search engines to return images with various semantic concepts, we also introduced a search result clustering (SRC)- based strategy to select those images which are more likely to be relevant to the content of music, using a naive Bayesian inference. Preliminary evaluations of the proposed approach on around 100 popular English music songs have shown promising results.
Experimental and theoretical investigation of backward-facing step flow

Laser-Doppler measurements of velocity distribution and reattachment length are reported downstream of a single backward-facing step mounted in a two-dimensional channel. Results are presented for laminar, transitional and turbulent flow of air in a Reynolds-number range of 70 < Re < 8000. The experimental results show that the various flow regimes are characterized by typical variations of the separation length with Reynolds number. The reported laser-Doppler measurements do not only yield the expected primary zone of recirculating flow attached to the backward-facing step but also show additional regions of flow separation downstream of the step and on both sides of the channel test section. These additional separation regions have not been previously reported in the literature. Although the high aspect ratio of the test section (1:36) ensured that the oncoming flow was fully developed and two-dimensional, the experiments showed that the flow downstream of the step only remained two-dimensional at low and high Reynolds numbers. The present study also included numerical predictions of backward-facing step flow. The two-dimensional steady differential equations for conservation of mass and momentum were solved. Results are reported and are compared with experiments for those Reynolds numbers for which the flow maintained its two-dimensionality in the experiments. Under these circumstances, good agreement between experimental and numerical results is obtained.
Brain–Computer Interface for Neurorehabilitation of Upper Limb After Stroke

Current rehabilitation therapies for stroke rely on physical practice (PP) by the patients. Motor imagery (MI), the imagination of movements without physical action, presents an alternate neurorehabilitation for stroke patients without relying on residue movements. However, MI is an endogenous mental process that is not physically observable. Recently, advances in brain-computer interface (BCI) technology have enabled the objective detection of MI that spearheaded this alternate neurorehabilitation for stroke. In this review, we present two strategies of using BCI for neurorehabilitation after stroke: detecting MI to trigger a feedback, and detecting MI with a robot to provide concomitant MI and PP. We also present three randomized control trials that employed these two strategies for upper limb rehabilitation. A total of 125 chronic stroke patients were screened over six years. The BCI screening revealed that 103 (82%) patients can use electroencephalogram-based BCI, and 75 (60%) performed well with accuracies above 70%. A total of 67 patients were recruited to complete one of the three RCTs ranging from two to six weeks of which 26 patients, who underwent BCI neurorehabilitation that employed these two strategies, had significant motor improvement of 4.5 measured by Fugl-Meyer Motor Assessment of the upper extremity. Hence, the results demonstrate clinical efficacy of using BCI as an alternate neurorehabilitation for stroke.
Caenorhabditis elegans Cyclin D/CDK4 and Cyclin E/CDK2 Induce Distinct Cell Cycle Re-Entry Programs in Differentiated Muscle Cells

Cell proliferation and differentiation are regulated in a highly coordinated and inverse manner during development and tissue homeostasis. Terminal differentiation usually coincides with cell cycle exit and is thought to engage stable transcriptional repression of cell cycle genes. Here, we examine the robustness of the post-mitotic state, using Caenorhabditis elegans muscle cells as a model. We found that expression of a G1 Cyclin and CDK initiates cell cycle re-entry in muscle cells without interfering with the differentiated state. Cyclin D/CDK4 (CYD-1/CDK-4) expression was sufficient to induce DNA synthesis in muscle cells, in contrast to Cyclin E/CDK2 (CYE-1/CDK-2), which triggered mitotic events. Tissue-specific gene-expression profiling and single molecule FISH experiments revealed that Cyclin D and E kinases activate an extensive and overlapping set of cell cycle genes in muscle, yet failed to induce some key activators of G1/S progression. Surprisingly, CYD-1/CDK-4 also induced an additional set of genes primarily associated with growth and metabolism, which were not activated by CYE-1/CDK-2. Moreover, CYD-1/CDK-4 expression also down-regulated a large number of genes enriched for catabolic functions. These results highlight distinct functions for the two G1 Cyclin/CDK complexes and reveal a previously unknown activity of Cyclin D/CDK-4 in regulating metabolic gene expression. Furthermore, our data demonstrate that many cell cycle genes can still be transcriptionally induced in post-mitotic muscle cells, while maintenance of the post-mitotic state might depend on stable repression of a limited number of critical cell cycle regulators.
The Consensus Group Technique in Social Research

The Consensus Group Technique is a new method for carrying out qualitative research in small groups. It was designed particularly for use in participative research, by which relatively untrained moderators may obtain more reliable data than is possible in these circumstances with focus groups. The principle of consensus groups is almost the opposite from the principle of surveys: In consensus groups, instead of using questions with fixed wording and determining the distribution of multiple-choice answers, a criterion level of agreement is set (usually around 75%) and statements are modified to determine whether the criterion level can be met.
A Novel Technique to Solve Mathematical Model of Pressure Swing Adsorption System for Oxygen Separation from Air

The mathematical modeling of a Pressure Swing Adsorption (PSA) system is discussed in detail for the Skarstrom cycle of two-bed process. The system is used to get pure oxygen product from the air with the use of zeolite 13X as an adsorbent. There are complex partial differential equations (pdes) which may not solve by analytical methods. There is no provision for solving it in any other software other than Matlab. All the equations are rearranged and written into dimensionless quantities, to make it easier. It is a novel technique of solving these complex PDEs. After that we have converted these PDEs into ODEs (Ordinary Differential Equations) by using OCFE (Orthogonal Collocation on Finite Elements) method. Now, these ODEs can be solved using different solvers like ode23, ode45, ode113, ode15s, ode23s, ode23t, ode23tb. The results obtained by this model will be compared to real industrial data.
Synapse Innervation and Associative Memory Cell Are Recruited for Integrative Storage of Whisker and Odor Signals in the Barrel Cortex through miRNA-Mediated Processes

Associative learning is a common way for information acquisition, and the integrative storage of multiple associated signals is essential for associative thinking and logical reasoning. In terms of the cellular mechanism for associative memory, our studies by behavioral task and cellular imaging demonstrate that paired whisker and odor stimulations lead to odorant-induced whisker motion and associative memory cell recruitment in the barrel cortex (BC), which is driven presumably by synapse innervation from co-activated sensory cortices. To confirm these associative memory cells and synapse innervations essential for associative memory and to examine their potential mechanisms, we studied a causal relationship between epigenetic process and memory cell/synapse recruitment by manipulating miRNAs and observing the changes from the recruitments of associative memory cells and synapse innervations to associative memory. Anti-miRNA-324 and anti-miRNA-133a in the BC significantly downregulate new synapse innervation, associative memory cell recruitment and odorant-induced whisker motion, where Tau-tubulin kinase-1 expression is increased. Therefore, the upregulated miRNA-324 in associative learning knocks down Ttbk1-mediated Tau phosphorylation and microtubule depolymerization, which drives the balance between polymerization and depolymerization toward the axon prolongation and spine stabilization to initiate new synapse innervations and to recruit associative memory cells.
PaperPulse: An Integrated Approach for Embedding Electronics in Paper Designs

We present PaperPulse, a design and fabrication approach that enables designers without a technical background to produce standalone interactive paper artifacts by augmenting them with electronics. With PaperPulse, designers overlay pre-designed visual elements with widgets available in our design tool. PaperPulse provides designers with three families of widgets designed for smooth integration with paper, for an overall of 20 different interactive components. We also contribute a logic demonstration and recording approach, Pulsation, that allows for specifying functional relationships between widgets. Using the final design and the recorded Pulsation logic, PaperPulse generates layered electronic circuit designs, and code that can be deployed on a microcontroller. By following automatically generated assembly instructions, designers can seamlessly integrate the microcontroller and widgets in the final paper artifact.
Cdk5 Regulates Activity-Dependent Gene Expression and Dendrite Development

The proper growth and arborization of dendrites in response to sensory experience are essential for neural connectivity and information processing in the brain. Although neuronal activity is important for sculpting dendrite morphology, the underlying molecular mechanisms are not well understood. Here, we report that cyclin-dependent kinase 5 (Cdk5)-mediated transcriptional regulation is a key mechanism that controls activity-dependent dendrite development in cultured rat neurons. During membrane depolarization, Cdk5 accumulates in the nucleus to regulate the expression of a subset of genes, including that of the neurotrophin brain-derived neurotrophic factor, for subsequent dendritic growth. Furthermore, Cdk5 function is mediated through the phosphorylation of methyl-CpG-binding protein 2, a key transcriptional repressor that is mutated in the mental disorder Rett syndrome. These findings collectively suggest that the nuclear import of Cdk5 is crucial for activity-dependent dendrite development by regulating neuronal gene transcription during neural development. SIGNIFICANCE STATEMENT Neural activity directs dendrite development through the regulation of gene transcription. However, how molecular signals link extracellular stimuli to the transcriptional program in the nucleus remains unclear. Here, we demonstrate that neuronal activity stimulates the translocation of the kinase Cdk5 from the cytoplasmic compartment into the nucleus; furthermore, the nuclear localization of Cdk5 is required for dendrite development in cultured neurons. Genome-wide transcriptome analysis shows that Cdk5 deficiency specifically disrupts activity-dependent gene transcription of bdnf. The action of Cdk5 is mediated through the modulation of the transcriptional repressor methyl-CpG-binding protein 2. Therefore, this study elucidates the role of nuclear Cdk5 in the regulation of activity-dependent gene transcription and dendritic growth.
L2 Regularization for Learning Kernels

The choice of the kernel is critical to the success of many learning algorithms but it is typically left to the user. Instead, the training data can be used to learn the kernel by selecting it out of a given family, such as that of non-negative linear combinations of p base kernels, constrained by a trace or L1 regularization. This paper studies the problem of learning kernels with the same family of kernels but with an L2 regularization instead, and for regression problems. We analyze the problem of learning kernels with ridge regression. We derive the form of the solution of the optimization problem and give an efficient iterative algorithm for computing that solution. We present a novel theoretical analysis of the problem based on stability and give learning bounds for orthogonal kernels that contain only an additive term O(√p/m) when compared to the standard kernel ridge regression stability bound. We also report the results of experiments indicating that L1 regularization can lead to modest improvements for a small number of kernels, but to performance degradations in larger-scale cases. In contrast, L2 regularization never degrades performance and in fact achieves significant improvements with a large number of kernels.
A directory service for configuring high-performance distributed computations

High-performance execution in distributed computing environments often requires careful selection and configuration not only of computers, networks, and other resources but also of the protocols and algorithms used by applications. Selection and configuration in turn require access to accurate, up-to-date information on the structure and state of available resources. Unfortunately no standard mechanism exists for organizing or accessing such information. Consequently different tools and applications adopt ad hoc mechanisms, or they compromise their portability and performance by using default configurations. We propose a Metacomputing Directory Service that provides efficient and scalable access to diverse, dynamic, and distributed information about resource structure and state. We define an extensible data model to represent required information and present a scalable, high-performance, distributed implementation. The data representation and application programming interface are adopted from the Lightweight Directory Access Protocol; the data model and implementation are new. We use the Globus distributed computing toolkit to illustrate how this directory service enables the development of more flexible and efficient distributed computing services and applications.
Interrogation of a Long-Period Grating Sensor by a Thermally Tunable Arrayed Waveguide Grating

An interrogation technique for a long-period grating (LPG) sensor is studied theoretically and experimentally. By employing a thermally tunable arrayed waveguide grating (AWG), the center wavelength of the LPG sensor is successfully measured using the linear temperature dependence of the AWG transmission wavelengths. Initial results show that the proposed interrogation technique can provide a resolution of 1 pm and interrogation range of 25 nm. Furthermore, this technique has the potential of being packaged into a low-cost and compact-size device.