Miracle-dz/UniFAR-FTUs huggingface dataset:
Impulse Response Matching and GMM Estimations in Weakly Identi ed Models

I compare the ef ciency of IRM and GMM in estimating the parameters of a hybrid new Keynesian general equilibrium model, using a Monte Carlo study. For the IRM estimation, I start by choosing the best decomposition for the identi cation of structural shocks in a VAR. This is done by comparing the estimated responses from small simulated samples, obtained from different identi cation schemes, with the model impulse responses for the true parameter values. The results of this experiment expand on those of Chari, Kehoe and McGrattan (2005) and also Canova and Sala (2006). Next, I compare parameters, as estimated by IRM, with those produced by GMM and nd that in the absence of autocorrelation in structural shocks, GMM yields more precise estimates. However, this result is reversed for higher degrees of autocorrelation. In this case, GMM starts to suffer from a weak instruments problem, whereas IRM bene ts from the longer response to shocks. JEL Codes: C13
Clause-Learning Algorithms with Many Restarts and Bounded-Width Resolution

We offer a new understanding of some aspects of practical SAT-solvers that are based on DPLL with unit-clause propagation, clause-learning, and restarts. We do so by analyzing a concrete algorithm which we claim is faithful to what practical solvers do. In particular, before making any new decision or restart, the solver repeatedly applies the unit-resolution rule until saturation, and leaves no component to the mercy of non-determinism except for some internal randomness. We prove the perhaps surprising fact that, although the solver is not explicitly designed for it, with high probability it ends up behaving as width-k resolution after no more than O(n2k+2) conflicts and restarts, where n is the number of variables. In other words, width-k resolution can be thought of as O(n2k+2) restarts of the unit-resolution rule with learning.
A Digital Current-Mode Control Technique for DC–DC Converters

The objective of this paper is to propose a simple digital current mode control technique for dc-dc converters. In the proposed current-mode control method, the inductor current is sampled only once in a switching period. A compensating ramp is used in the modulator to determine the switching instant. The slope of the compensating ramp is determined analytically from the steady-state stability condition. The proposed digital current-mode control is not predictive, therefore the trajectory of the inductor current during the switching period is not estimated in this method, and as a result the computational burden on the digital controller is significantly reduced. It therefore effectively increases the maximum switching frequency of the converter when a particular digital signal processor is used to implement the control algorithm. It is shown that the proposed digital method is versatile enough to implement any one of the average, peak, and valley current mode controls by adjustment of the sampling instant of the inductor current with respect to the turn-on instant of the switch. The proposed digital current-mode control algorithm is tested on a 12-V input and 1.5-V, 7-A output buck converter switched at 100kHz and experimental results are presented
WHERE DID THE ANGER GO? THE ROLE OF CONTEXT IN INTERPRETING EMOTION IN SPEECH

Context has greater explanatory force regarding the perception of emotions in speech than any causative association we may attempt to make between phonetic features and psychological labels. Informants, when asked to judge whether a speaker sounds angry or not, make different decisions according to whether they hear utterances in-isolation or in-context. There was a strong tendency for ‘anger’ to be heard in the isolated extracts, but not in the ‘in-context’ forms.
Clinical trial data in support of changing guidelines in osteoarthritis treatment

Goals for the management of osteoarthritis (OA) emphasize pain relief, reduction of inflammation, and improvement in functioning. Among pharmacological pain management interventions, nonsteroidal anti-inflammatory drugs (NSAIDs) are frequently recommended as the most effective treatment option for OA. However, the use of traditional oral NSAIDs is associated with risk of serious adverse events involving the gastrointestinal, cardiovascular, and renal systems. Topical NSAIDs are an alternative with well-established tolerability and efficacy in the treatment of OA of the knee or hand. While the management of OA pain is evolving toward the more widespread use of topical NSAIDs, some OA management guidelines have yet to incorporate these agents in their recommendations. This review examines the efficacy and tolerability of topical NSAIDs, their current placement in OA management guidelines, and their potential role in enabling pain specialists to provide individualized care for their patients with OA.
DynaRIA: A Tool for Ajax Web Application Comprehension

Thanks to Rich Internet Applications (RIAs) with their enhanced interactivity, responsiveness and dynamicity, the user experience in the Web 2.0 is becoming more and more appealing and user-friendly. At the same time, the dynamic nature of RIAs, and the heterogeneous technologies, frameworks, communication models used for implementing them negatively affect their analyzability and understandability, so that specific software techniques and tools are needed for supporting their comprehension. This paper presents DynaRIA, a tool for the comprehension of RIAs implemented in Ajax that is based on dynamic analysis and provides functionalities for recording and analyzing user sessions from several perspectives, and producing various types of abstractions and visualizations about the run-time behaviour of the application.
Microstructure and Properties of Liquid Phase Sintered SiC/SiC Composites

SiC/SiC composites with attractive thermo-mechanical properties and gas tightness have been developed through a combination of transient liquid-phase sintering of nano-phase SiC powders mixed with oxide additives and advanced near-stoichiometric SiC fibers with an appropriate coating. The mechanical properties generally improved with the increased sintering temperature and pressure in the range employed in the present experiment. The mechanical property improvement was attributed to the reduced intra-fiber bundle matrix porosity and the promoted matrix sintering. The matrix consisted mostly of even-sized SiC crysta grains both in fiber-bundle and fiber-free regions. Thermal conductivity is likely be determined by the grain boundary scattering. The thermo-mechanical properties of the composites will be tailorable by controlling the matrix microstructure through varying the sintering temperature and time. The tailorability will probably be limited by interfacial structure integrity and the fibers' heat resistance.
Transmission Techniques for Ultra Dense Wavelength Division Multiplexing By Using Two Optical Amplifiers in Nonlinear Optical Networks

------------------------------------------------------------------ABSTRACT-------------------------------------------------------------In the present paper, the problem amplification techniques of ultra dense wavelength division multiplexing (UDWDM) in nonlinear optical networks are investigated through five transmission techniques. The impact of tailoring of chirped pulses of different temporal waveforms is investigated in a normal dispersion fiber. The set of multiplexed signals are tailored in a different a subset to assure approximately the same output level of power to hold the signal-to-noise ratio at the same level. Moreover, three different transmission techniques, namely, soliton propagation, maximum time division multiplexing (MTDM) and Shannon capacity, are employed where successive section of alternating dispersion are used as a technique to manage the dispersion. Distributed Raman amplifiers as well as Erbium doped fiber amplifier are engaged to maximize the repeater spacing. We have succeeded to multiplex 2400 (UDWDM) channels in the optical range 1.45  1.65 μm with channel spacing ranging from 0.3 up to 0.6 nm where each channel has its own characteristic parameters of loss, dispersion, and amplification. The channels are divided into sub-groups ( each of 4, 5, 6, 7, .,24 ) where the technique of space division multiplexing (SDM) is applied. The multispan effects of Kerr nonlinearity and amplifier noise on Shannon channel capacity of dispersion-free nonlinear fiber is considered as a ceiling value for the sake of comparison. The case of soliton with modified Raman amplification via parametric gain also is investigated. Each link has special chemical structure, optical signals power, and optical Raman pumping. The cable contains {4, 5, 6, 7, . , 24} links in SDM. It has been shown that the modified Raman gain yields higher effects on the variable under consideration if compared with the conventional Raman gain. The number of links is in positive correlations with the set of effects {Repeater spacing, Soliton product, MTDM product}. In general Shannon product is the ceiling but it undergoes a maximum value at twelve links. The Chirping product also possesses a maximum at 8 links.
Flex-Hets differentially induce apoptosis in cancer over normal cells by directly targeting mitochondria

Flex-Het drugs induce apoptosis in multiple types of cancer cells, with little effect on normal cells. This apoptosis occurs through the intrinsic mitochondrial pathway accompanied by generation of reactive oxygen species (ROS). The objective of this study was to determine if direct or indirect targeting of mitochondria is responsible for the differential sensitivities of cancer and normal cells to Flex-Hets. Mitochondrial effects and apoptosis were measured using JC-1 and Annexin V-FITC dyes with flow cytometry. Bcl-2, Bcl-xL, and Bax were measured by Western blot. Flex-Hets induced mitochondrial swelling and apoptosis in ovarian cancer cell lines but had minimal to no effects in a variety of normal cell cultures, including human ovarian surface epithelium. Effects on inner mitochondrial membrane (IMM) potential were variable and did not occur in normal cells. Two different antioxidants, administered at concentrations shown to quench intracellular and mitochondrial ROS, did not alter Flex-Het–induced mitochondrial swelling, loss of IMM potential, or apoptosis. Inhibition of protein synthesis with cycloheximide also did not prevent Flex-Het mitochondrial or apoptosis effects. Bcl-2 and Bcl-xL levels were decreased in an ovarian cancer cell line but increased in a normal culture, whereas Bax expression was unaffected by Flex-Hets treatment. In conclusion, ROS seems to be a consequence rather than a cause of mitochondrial swelling. The differential induction of apoptosis in cancer versus normal cells by Flex-Hets involves direct targeting of mitochondria associated with alterations in the balance of Bcl-2 proteins. This mechanism does not require IMM potential, ROS generation, or protein synthesis. [Mol Cancer Ther 2007;6(6):1814–22]
Study of Severe Hepatitis Treated with a Hybrid Artificial Liver Support System

Artificial liver support system (ALSS) has been used to treat hepatic failure and has significantly decreased the mortality. TECA hybrid artificial liver support system (TECA-HALSS), which combines the hollow fiber bioreactor with a plasma exchange circuit, was used to assess the efficacy, safety and feasibility in treating severe hepatitis patients. The hybrid artificial liver support system (HALSS) consists of a bioreactor containing more than 5 ×109 porcine hepatocytes and plasma exchange device. Fifteen patients with severe hepatitis were treated with this hybrid system. All patients experienced a reduction in symptoms such as fatigue, abdominal distention or ascites. After each treatment serum total bilirubin decreased markedly while prothrombin activity increased. There were ten patients whose progress of hepatocyte necrosis was stopped after HALSS treatment, and finally they recovered completely. One patient received liver transplantation after HALSS therapy and survived. No serious adverse events were noted in the fifteen patients.
A twofold quantum delayed-choice experiment in a superconducting circuit

A twofold delayed-choice experiment was performed, where the behavior of a quantum system was a posteriori chosen twice. Wave-particle complementarity lies at the heart of quantum mechanics. To illustrate this mysterious feature, Wheeler proposed the delayed-choice experiment, where a quantum system manifests the wave- or particle-like attribute, depending on the experimental arrangement, which is made after the system has entered the interferometer. In recent quantum delayed-choice experiments, these two complementary behaviors were simultaneously observed with a quantum interferometer in a superposition of being closed and open. We suggest and implement a conceptually different quantum delayed-choice experiment by introducing a which-path detector (WPD) that can simultaneously record and neglect the system’s path information, but where the interferometer itself is classical. Our experiment is realized with a superconducting circuit, where a cavity acts as the WPD for an interfering qubit. Using this setup, we implement the first twofold delayed-choice experiment, which demonstrates that the system’s behavior depends not only on the measuring device’s configuration that can be chosen even after the system has been detected but also on whether we a posteriori erase or mark the which-path information, the latter of which cannot be revealed by previous quantum delayed-choice experiments. Our results represent the first demonstration of both counterintuitive features with the same experimental setup, significantly extending the concept of quantum delayed-choice experiment.
Zinc oxide nanowires for biosensor applications

The current paper is devoted to the fabrication and optimisation of ZnO nanowire (ZnONW) arrays for electrochemical glucose biosensor fabrication. The ZnO nanowires were fabricated by a two-step combination method. This includes radio-frequency (RF) sputtering of the ZnO seeding layer and hydrothermal growth of the nanowires in a solution containing zinc nitrate hexahydrate. Glucose oxidase has been immobilised on the nanowires, for use as the biorecognition molecule. The sensing characteristics of the biosensors based on this fabrication methodology were investigated in phosphate buffer solution using electrochemical techniques.
EVNDN: Enhanced vehicular named data networking

Named Data Networking (NDN) [1], [2] is a newly proposed architecture to enhance the data distribution in the network. Thus, it is a new paradigm of communication based on the data regardless the host address. Therefore, NDN can be adapted on the Vehicular Ad hoc NETworks (VANETs) to improve safety and comfort of the road users. This paper adapts the NDN to VANETs and proposes an amelioration of R-NDN [3] architecture. Our proposed solution called EVNDN aims to reduce the packets collision and the error rate through a new mechanism of relay node selection during flooding to eliminate the retransmission of packets. Simulation results confirm the efficiency and suitability for our proposed amelioration.
Approximateab initiocalculation of vibrational properties of hydrogenated amorphous silicon with inner voids

We have performed an approximate ab initio calculation of vibrational properties of hydrogenated amorphous silicon $(a\ensuremath{-}\mathrm{S}\mathrm{i}:\mathrm{H})$ using a molecular dynamics method. A 216-atom model for pure amorphous silicon $(a\ensuremath{-}\mathrm{Si})$ has been employed as a starting point for our $a\ensuremath{-}\mathrm{S}\mathrm{i}:\mathrm{H}$ models with voids that were made by removing a cluster of silicon atoms out of the bulk and terminating the resulting dangling bonds with hydrogens. Our calculation shows that the presence of voids leads to localized low-energy $(30\char21{}50 {\mathrm{cm}}^{\ensuremath{-}1})$ states in the vibrational spectrum of the system. The nature and localization properties of these states are analyzed by various visualization techniques.
Unit Quaternion-Based Output Feedback for the Attitude Tracking Problem

In this note, we propose a quaternion-based dynamic output feedback for the attitude tracking problem of a rigid body without velocity measurement. Our approach consists of introducing an auxiliary dynamical system whose output (which is also a unit quaternion) is used in the control law together with the unit quaternion representing the attitude tracking error. Roughly speaking, the necessary damping that would have been achieved by the direct use of the angular velocity can be achieved, in our approach, by the vector part \mathtilde q of the error signal between the output of the auxiliary system and the unit quaternion tracking error. The resulting velocity-free control scheme guarantees almost global asymptotic stability which is as strong as the topology of the motion space can permit. In the regulation case, our control law is a pure quaternion feedback (i.e., consisting of two terms that are vector parts of unit-quaternion), and hence, the control torques are naturally bounded by the control gains. Simulation results are provided to show the effectiveness of the proposed control scheme.
Concept formation in numeric domains

COBWEB is a concept formation system that organizes observations into a classification tree. However, it can only handles symbolic data. COBWEB/3 handles numeric data assuming a normal distribution of attribute values. However, COBWEB/Q requires a userspecified acuity value that has to be carefully tuned to obtain the optimal concept hierarchy. However, single acuity value may not be appropriate to all attributes which may have various ranges of values. In this paper, we show how important the normalization of each attribute is, and present an algorithm that can properly handle symbolic and/or numeric data. Topics : Artificial Intelligence, Machine Learning
Early and late integration of audio features for automatic video description

This paper presents our approach to improve video captioning by integrating audio and video features. Video captioning is the task of generating a textual description to describe the content of a video. State-of-the-art approaches to video captioning are based on sequence-to-sequence models, in which a single neural network accepts sequential images and audio data, and outputs a sequence of words that best describe the input data in natural language. The network thus learns to encode the video input into an intermediate semantic representation, which can be useful in applications such as multimedia indexing, automatic narration, and audio-visual question answering. In our prior work, we proposed an attention-based multi-modal fusion mechanism to integrate image, motion, and audio features, where the multiple features are integrated in the network. Here, we apply hypothesis-level integration based on minimum Bayes-risk (MBR) decoding to further improve the caption quality, focusing on well-known evaluation metrics (BLEU and METEOR scores). Experiments with the YouTube2Text and MSR-VTT datasets demonstrate that combinations of early and late integration of multimodal features significantly improve the audio-visual semantic representation, as measured by the resulting caption quality. In addition, we compared the performance of our method using two different types of audio features: MFCC features, and the audio features extracted using SoundNet, which was trained to recognize objects and scenes from videos using only the audio signals.
Extremely small-core photonic crystal fiber fusion splicing with a single-mode fiber

We present a low-loss fusion splicing of a non-linear photonic-crystal fiber (NL-PCF) with a single-mode fiber (SMF), helped by an intermediate fiber, using a electric-arc splicer. We also analysed the splice loss between SMF and intermediate fiber, as a function of the electrical discharge duration, to achieve a low-loss transition between SMF and intermediate fiber, through a thermally expanded core splice (TEC). The NL-PCF has a external cladding diameter of 105 μm, a core diameter of 1.7 μm and mode-field diameter (MFD) of 1.5 μm. We also performed mechanical strength tests to verify the robustness of the splice joints obtained.
Computational biology of cardiac myocytes: proposed standards for the physiome

SUMMARY Predicting information about human physiology and pathophysiology from genomic data is a compelling, but unfulfilled goal of post-genomic biology. This is the aim of the so-called Physiome Project and is, undeniably, an ambitious goal. Yet if we can exploit even a small proportion of the rich and varied experimental data currently available, significant insights into clinically important aspects of human physiology will follow. To achieve this requires the integration of data from disparate sources into a common framework. Extrapolation of available data across species, laboratory techniques and conditions requires a quantitative approach. Mathematical models allow us to integrate molecular information into cellular, tissue and organ-level, and ultimately clinically relevant scales. In this paper we argue that biophysically detailed computational modelling provides the essential tool for this process and, furthermore, that an appropriate framework for annotating, databasing and critiquing these models will be essential for the development of integrative computational biology.
Prospects for usage-based computational models of grammatical development: argument structure and semantic roles.

UNLABELLED The computational modeling of language development has enabled researchers to make impressive strides toward achieving a comprehensive psychological account of the processes and mechanisms whereby children acquire their mother tongues. Nevertheless, the field's primary focus on distributional information has lead to little progress in elucidating the processes by which children learn to compute meanings beyond the level of single words. This lack of psychologically motivated computational work on semantics poses an important challenge for usage-based computational accounts of acquisition in particular, which hold that grammatical development is closely tied to meaning. In the present review, we trace some initial steps toward answering this challenge through a survey of existing computational models of grammatical development that incorporate semantic information to learn to assign thematic roles and acquire argument structure. We argue that the time is ripe for usage-based computational accounts of grammatical development to move beyond purely distributional features of the input, and to incorporate information about the objects and actions observable in the learning environment. To conclude, we sketch possible avenues for extending previous approaches to modeling the role of semantics in grammatical development. WIREs Cogn Sci 2014, 5:489-499. doi: 10.1002/wcs.1295 For further resources related to this article, please visit the WIREs website. CONFLICT OF INTEREST The authors have declared no conflicts of interest for this article.
Real-Time Path Planning for Humanoid Robot Navigation

We present a data structure and an algorithm for real-time path planning of a humanoid robot. Due to the many degrees of freedom, the robots shape and available actions are approximated for finding solutions efficiently. The resulting 3 dimensional configuration space is searched by the A* algorithm finding solutions in tenths of a second on lowperformance, embedded hardware. Experimental results demonstrate our solution for a robot in a world containing obstacles with different heights, stairs and a higher-level platform.