Miracle-dz/UniFAR-FTUs huggingface dataset:
Doppler blood flow signal analysis meets traditional Chinese pulse diagnosis

In traditional Chinese pulse diagnosis (TCPD), diseases of internal organs can be detected by recognizing pulse waveform patterns of wrist radial arterial. However pulse waveform analysis, for which Doppler diagnosis is a powerful tool, is limited to cardiovascular diseases. This paper tries to fill the gap between TCPD and Doppler diagnosis by applying signal analysis and pattern recognition technologies to Doppler blood flow signals (DBFS's) of wrist radial arterial, which are recorded from both hands of healthy people, gastritis and cholecystitis patients. DBFS's are classified using the features proposed by an L2-soft margin support vector machine (L2-SVM): five clinical Doppler parameters (DP), wavelet energies (WE), wavelet packet energies (WPE), and piecewise axially integrated bispectra (PAIB). 5-fold cross validation is used for performance evaluation. The sick are differentiated from the healthy with an accuracy of about 80% using DP, WE and WPE, while the classification rate between gastritis and cholecystitis reaches 100%. Using PAIB, ether two groups of subjects are classified with accuracy greater than 93%. Gastritis is more accurately recognized than cholecystitis, while the latter is recognized with a higher accuracy on data from the left hand than right. Though the sample size is relatively small, we still argue that the methods proposed here are effective and could serve as an assisstive tool for TCPD.
Predictive model for minimal hepatic encephalopathy based on cerebral functional connectivity

Minimal hepatic encephalopathy (MHE) is a common neurocognitive complication of liver cirrhosis, which have few recognizable clinical symptoms. Previous functional magnetic resonance imaging (fMRI) studies have found that widespread cortical and subcortical functional connectivity (FC) changes were significantly in patients with MHE. The goals of this study were twofold: 1) to construct predictive models for MHE, based on brain regional functional connectivity, 2) and to test feature selection method on p-value ranker based kernel principle component analysis (kPCA). Our study included thirty-two cirrhotic patients with MHE and twenty age-, gender-, and eduction-matched healthy controls. Using 1.5T MR, we obtained resting-state fMRI for each subject. Functional connectivities between 116 pairs of brain regions in patients with MHE were compared with those in control participants. Then, p-value ranker based kPCA was applied in feature selection step to reduce the dimension of input data. The best parameters of feature selection were chose based on 10-fold cross-validation of vector machines (SVMs). Finally, We found FC-based diagnostic model was accurate in differing MHE from normal controls with 86.5% accuracy, 88% specifity and 85% sensitivity.
Debt, Deleveraging and the Liquidity Trap

In this paper we present a simple New Keynesian-style model of debt-driven slumps -- that is, situations in which an overhang of debt on the part of some agents, who are forced into rapid deleveraging, is depressing aggregate demand. Making some agents debt-constrained is a surprisingly powerful assumption: Fisherian debt deflation, the possibility of a liquidity trap, the paradox of thrift, a Keynesiantype multiplier, and a rationale for expansionary fiscal policy all emerge naturally from the model. We argue that this approach sheds considerable light both on current economic difficulties and on historical episodes, including Japan's lost decade (now in its 18th year) and the Great Depression itself.
Distributed Kalman Filtering : Weak Consensus Under Weak Detectability

The paper presents the gossip interactive Kalman filter (GIKF) for distributed Kalman filtering for networked systems and sensor networks, where intersensor communication and observations occur at the same time-scale. The communication among sensors is random; each sensor occasionally exchanges its filtering state information with a neighbor depending on the availability of the appropriate network link. We show that under a weak distributed detectability condition: 1) the GIKF error process remains stochastically bounded, irrespective of the instability of the random process dynamics; and 2) the network achieves weak consensus, i.e., the conditional estimation error covariance at a (uniformly) randomly selected sensor converges in distribution to a unique invariant measure on the space of positive semidefinite matrices (independent of the initial state). To prove these results, we interpret the filtering states (estimates and error covariances) at each node in the GIKF as stochastic particles with local interactions. We analyze the asymptotic properties of the error process by studying as a random dynamical system the associated switched (random) Riccati equation, the switching being dictated by a nonstationary Markov chain on the network graph.
Kolmogorov-Burgers Model for Star-forming Turbulence

The process of star formation in interstellar molecular clouds is believed to be controlled by driven supersonic magnetohydrodynamic turbulence. We suggest that in the inertial range, such turbulence obeys the Kolmogorov law, while in the dissipative range, it behaves as Burgers turbulence developing shock singularities. On the base of the She-Lévêque analytical model, we then predict the velocity power spectrum in the inertial range to be Ek ~ k-1.74. This result agrees well with recent numerical findings by Padoan & Nordlund and reproduces the observational Larson law ⟨u⟩ ~ l0.74. 0.76. The application of the model to more general dissipative structures with higher fractal dimensionality is discussed.
The importance of phylogenetic scale in tests of Bergmann's and Rapoport's rules: lessons from a clade of South American lizards

We tested for the occurrence of Bergmann's rule, the pattern of increasing body size with latitude, and Rapoport's rule, the positive relationship between geographical range size and latitude, in 34 lineages of Liolaemus lizards that occupy arid regions of the Andean foothills. We tested the climatic‐variability hypothesis (CVH) by examining the relationship between thermal tolerance breadth and distribution. Each of these analyses was performed varying the level of phylogenetic inclusiveness. Bergmann's rule and the CVH were supported, but Rapoport's rule was not. More variance in the data for Bergmann's rule and the CVH was explained using species belonging to the L. boulengeri series rather than all species, and inclusion of multiple outgroups tended to obscure these macroecological patterns. Evidence for Bergmann's rule and the predicted patterns from the CVH remained after application of phylogenetic comparative methods, indicating a greater role of ecological processes rather than phylogeny in shaping the current species distributions of these lizards.
Control and data channel resource allocation in macro-femto Heterogeneous Networks

This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macrocells and femtocells sharing the same frequency band. The focus is to devise an optimised policy for femtocells' access to the shared spectrum, in terms of femtocell transmissions, in order to keep femto users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro-cell users in the vicinity of femtocells is provided. Both data and control channel constraints are considered, to insure that not only the macro-cell users' data rate demands are meet, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. The problem is addressed by our proposed linear binary integer programming heuristic algorithm and the performance is compared with the conventional Reuse-1 scheme. Results show a negligible drop in femtocell performance for our proposed scheme, as a trade-off for ensuring all macro users data rate demands when Reuse-1 scheme can even lead up to 40% outage. Discussion is also presented for the implementation possibility of our proposed in a practical LTE network.
Identity Theft Detection Based on Neural Network Non-Linearity Identification in OFDM System

Confidentiality of the communication is extremely important in wireless networks due to the broadcast nature of the radio channel. The secrecy of the communication can be achieved via secure PHY layers or by using crypto techniques which need a pre-shared secret between the sender and the legal receiver. A technique has been proposed in literature to avoid preshared secrets based on the noise-pattern of the radio channel. However, when the channel frequency selectivity is low or the eavesdropper is located near to the victim, the key exchange may fail to achieve security. The eavesdropper can gain access to the secure communication and steal the identity of one of the two communicating nodes. In this paper, a technique for identity theft detection is proposed: the receiving node can detect unintended change of sender's identity. A Feed-Foward Neural Network is used to identify the non-linearities of the OFDM radio transceiver which are unique and characteristic of the transmitting and receiving devices. The simulation results show that the NN correctly detects the non linearities coefficients for pedestrian and high mobility terminals in the presence of severe fading and noise, providing a strong mean for radio signal identification to detect broken security.
Clarity: Cross Language Information Retrieval and Organisation of Text and Audio Documents, Ist-2000-25310 Ist R&d Project Shared-cost Rtd Project Human Language Technologies Project Officer: Yves Paternoster Clarity Cross Language Information Retrieval and Organization of Text and Audio Documents

for dissemination) The CLARITY project aims to explore the effectiveness of stylistic analysis in an implemented interactive information retrieval system. As reported in earlier literature, stylistic analysis seems to work well in post-hoc experimental settings. It has not been tested in real user tests, however. The CLARITY project aims to implement stylistic analysis tools and test them in ongoing interactive user tests. In addition, most experiments performed on use of stylistics in information retrieval have been exclusively on English-language material. The CLARITY project aims to extend the stylistic analysis functionality to languages other than English, notably the languages employed in the CLARITY project: Finnish, Swedish, Latvian, and Lithuanian. This report describes the current status of the reimplementation of known algorithms for the stylistic analysis of English and the establishment of the possibilites for the transfer of English language algorithms to Swedish. Finnish, Latvian, and Lithuanian are also part of the project, and effectiveness and usefulness of the tools for Finnish and for the Baltic languages can be extrapolated at this point.
Pathological Fear of Students in Mathematics: Gender Differences

The study explored the pathological fear in Mathematics of male and female college students. The study utilized the mixed method of research with 199 first year non-Math students as participants to determine the causes, effects, and ways of overcoming this fear. It made use of the cross-sectional design to explore the strategies of overcoming this pathological fear among the students. Results revealed that the students fear Math because of the influence of their friends, personal capacity, and the complex nature of Math. The male and female students differ in the prime cause of pathological fear. The cause as identified for the males is nature of the subject while personal capacity for the females. The students’ fear in Mathematics affects their performance in the subject. The main effect of the students’ fear in Math is recalling what had been learned when preparing for an examination. As a way of overcoming this fear, the female students cited that the teaching of mathematics should be made enjoyable. The male students suggested that they should be taught how mathematics is applied in everyday life situations. The students also need their parents’ support, encouragement, and motivation. On the part of the teachers, the students suggest the use of appropriate teaching strategies to make mathematics learning more meaningful.
Psychophysical Tests of the Hypothesis of a Bottom-Up Saliency Map in Primary Visual Cortex

A unique vertical bar among horizontal bars is salient and pops out perceptually. Physiological data have suggested that mechanisms in the primary visual cortex (V1) contribute to the high saliency of such a unique basic feature, but indicated little regarding whether V1 plays an essential or peripheral role in input-driven or bottom-up saliency. Meanwhile, a biologically based V1 model has suggested that V1 mechanisms can also explain bottom-up saliencies beyond the pop-out of basic features, such as the low saliency of a unique conjunction feature such as a red vertical bar among red horizontal and green vertical bars, under the hypothesis that the bottom-up saliency at any location is signaled by the activity of the most active cell responding to it regardless of the cell's preferred features such as color and orientation. The model can account for phenomena such as the difficulties in conjunction feature search, asymmetries in visual search, and how background irregularities affect ease of search. In this paper, we report nontrivial predictions from the V1 saliency hypothesis, and their psychophysical tests and confirmations. The prediction that most clearly distinguishes the V1 saliency hypothesis from other models is that task-irrelevant features could interfere in visual search or segmentation tasks which rely significantly on bottom-up saliency. For instance, irrelevant colors can interfere in an orientation-based task, and the presence of horizontal and vertical bars can impair performance in a task based on oblique bars. Furthermore, properties of the intracortical interactions and neural selectivities in V1 predict specific emergent phenomena associated with visual grouping. Our findings support the idea that a bottom-up saliency map can be at a lower visual area than traditionally expected, with implications for top-down selection mechanisms.
ARRG: real-world gossiping

Gossiping is an effective way of disseminating information in large dynamic systems. Until now, most gossiping algorithms have been designed and evaluated using simulations. However, these algorithms often cannot cope with several real-world problems that tend to be overlooked in simulations, such as node failures, message loss, non-atomicity ofinformation exchange, and firewalls. We explore the problems in designing and applying gossiping algorithms in real systems. Next to identifying the most prominent real-world problems and their current solutions, we introduce Actualized Robust Random Gossiping (ARRG), an algorithm specifically designed to take all of these real-world problems into account simultaneously. To address network connectivity problems such as firewalls we introduce a novel technique, the Fallback Cache. This cache can be applied to existing gossiping algorithms to improve their resilience against connectivity problems. We introduce a new metric, Perceived Network Size to measure a gossiping algorithm's effectiveness. In contrast to existing metrics, our new metric does not require global knowledge. Evaluation of ARRG and the Fallback Cache in a number of realistic scenarios shows that the proposed techniques significantly improve the performance of gossiping algorithms in networks with limited connectivity. Even in pathological situations, with 50% message loss and with 80% of the nodes behind a NAT, ARRG continues to work well. Existing algorithms fail in these circumstances.
Joint Channel Estimation and Synchronization with Inter-carrier Interference Reduction for OFDM

This paper proposes a pilot-aided joint channel estimation and synchronization scheme for burst-mode orthogonal frequency division multiplexing (OFDM) systems. The scheme eliminates the need of an IFFT block while keeping the low number of parameters to be estimated for low complexity without sacrificing the performance and convergence speed. For fast convergence and high performance, we develop a linearized cost function of the carrier frequency offset (CFO), sampling clock frequency offset (SFO) and channel impulse response (CIR) coefficients based on received signal samples and pilot tones in frequency domain and the corresponding recursive least square (RLS) estimation and tracking algorithm. For channel responses, CIR coefficients are estimated to benefit their low number and then transformed to the channel transfer function in order to keep low complexity. The ICI introduced by rotation due to CFO and SFO is analyzed and modeled, and a simple maximum-likelihood (ML) scheme based on the preamble is developed for coarse estimation of initial CFO and SFO values to be used in suppression of dominant ICI effects and in fine RLS estimation and tracking. Simulation results demonstrate that, in large practical ranges of CFO and SFO values, the proposed pilot-aided joint channel estimation and synchronization scheme provides a receiver performance remarkably close to the ideal case of perfect channel estimation and synchronization.
Word stress correlates in spontaneous child-directed speech in German

In this paper we focus on the use of acoustic as well as voice quality parameters to mark word stress in German. Our aim was to identify the speech parameters parents use to indicate word stress differences to their children. Therefore, mothers and their children were recorded during a period of at least one year while they performed a special playing task using word pairs that differ only in the position of word stress. The recorded target words were analyzed acoustically and with respect to voice quality. The results presented here concern the mothers’ productions of contrastive word stress, and we discuss our findings with respect to the results of previous studies investigating word stress. Our results provide further insight into the process of word stress acquisition in German. Index Terms: production, prosody, word stress, acoustics, voice quality
Understanding the data-processing challenges in Intelligent Vehicular Systems

Vehicular sensors able to perceive and measure the environment, ranging from in-vehicle sensors to speed cameras, are revolutionizing how technology can interact with our daily lives, enabling Intelligent Vehicular Systems (IVSs). These sensors generate large volumes of data which can reveal useful information for enhancing the sustainable development (through improved utilization of resources), as well as the safety and functionality of the system. In this context, a key challenge is to reduce the large data streams into manageable sets of valuable information in a real-time, reliable and cost-affordable fashion. Due to the data volume size and velocity, relying exclusively on traditional data processing systems, such as databases and batch processing, is no longer a suitable option, since it is not feasible to store the data to later process it. Moreover, careful decisions should be made to leverage the existing computing capacity, from embedded devices found in the IVSs to cloud infrastructures. In this paper we study trade-offs of possible options for data-stream processing models and computing infrastructures. Through building an experimental platform that emulates realistic components of a future deployable IVS and validating two different data-stream processing systems with a wellknown benchmark for IVSs, we study options and trade-offs in real-time data stream processing in IVS infrastructures. Our evaluation shows that existing data-stream processing models can be leveraged in different ways, based on the processing requirements.
Relationship between L-DOPA-induced reduction in motor and exploratory activity and degree of DAT binding in the rat

Purpose: The present study assessed the influence of L-DOPA administration on neostriatal dopamine (DA) transporter (DAT) binding in relation to motor and exploratory behaviors in the rat. Methods: Rats received injections of 5 mg/kg L-DOPA, 10 mg/kg L-DOPA or vehicle. Motor and exploratory behaviors were assessed for 30 min in an open field prior to administration of [123I]FP-CIT. Dopamine transporter binding was measured with small animal single-photon emission computed tomography (SPECT) 2 h after radioligand administration for 60 min. Results: Both L-DOPA doses significantly reduced DAT binding and led to significantly less head-shoulder motility and more sitting relative to vehicle. Moreover, 10 mg/kg L-DOPA induced less distance traveled and ambulation than 5 mg/kg L-DOPA. Analysis of time-behavior (t-b) curves showed that L-DOPA-treated animals relative to vehicle exhibited (1) a faster rate of increase in duration of sitting; (2) a slower rate of increase in duration of head-shoulder motility; and (3) a slower rate of decrease in frequency of head-shoulder motility. Conclusions: The reductions of striatal DAT binding after L-DOPA challenges reflected elevated concentrations of synaptic DA. L-DOPA-treated animals showed less head-shoulder motility and more sitting than vehicle-treated animals, indicating an association between less behavioral activity and increased availability of striatal DA. The faster increase of sitting duration to a higher final level and the slower increase of head-shoulder motility to a lower final level relative to controls may be interpreted in terms on behavioral habituation to a novel environment.
Experiments in determining the displacements and angular amplitudes of a hyper-redundant robot

This paper presents a series of experiments performed in order to determine the displacements and the angular amplitudes of a hyper-redundant robot. Two high-speed cameras were used to extract data related to the displacements of the robotic structure in order to obtain a control algorithm of the robot. Has been developed a parameterized model of the robot in order to observe the displacement and the rate of travel during its actuation.
Contact-induced change as an innovation

This paper explores a specific contact-induced change, that is, innovation, defined as structure that emerges as a consequence of contact between two languages and that diverges from the patterns of both the model language and the replica language. In other terms, these new innovated linguistic features are not created on the model of the model language. In this paper I investigate the development of new features as consequences of the contact between Purepecha, the replica language, and Spanish, the model language, with which it has been in contact for nearly five centuries. According to the types of contact-induced changes described by Thomason and Kaufman (1988), Purepecha presents a situation of intense contact and the characteristics of a shift situation, since the changes are mainly in phonology and morphosyntax (Chamoreau 2007, 2010).
Merging segmental, rhythic and fudamental frequency features for Automatic Language Identification

This paper deals with an approach to Automatic Language Identification based on rhythmic and fundamental frequency modeling. Experiments are performed on read speech for 5 European languages. They show that rhythm can be automatically extracted and is relevant in language identification: using cross-validation, 79% of correct identification is reached with 21 s. utterances The fundamental frequency modeling, tested in the same conditions (cross-validation), produces 50% of correct identification for the 21 s. utterances. The Vowel System Modeling gives an identification rate of 70% for the 21 s. utterances. Last, merging the three models slightly improves the identification rate.