Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnosing Parkinson by using artificial neural networks and support vector machines

Parkinson\'s Disease (PD) is the second most common neurodegenerative ai? ½iction only surpassed by Alzheimer\'s Disease (AD). Moreover, it is expected to increase in the next decade with accelerating treatment costs as a consequence. This situation leads us towards the need to develop a Decision Support System for PD. In this paper we propose methods based on ANNs and SVMs to aid the specialist in the diagnosis of PD. Data recorded during 195 examinations carried out on 31 patients was used to verify the capacity of the proposed system. The results show a high accuracy of around 90%.
On further reduction of complexity in tree pruning based sphere search

In this letter, we propose an extension of the probabilistic tree pruning sphere decoding (PTP-SD) algorithm that provides further improvement of the computational complexity with minimal extra cost and negligible performance penalty. In contrast to the PTP-SD that considers the tightening of necessary conditions in the sphere search using per-layer radius adjustment, the proposed method focuses on the sphere radius control strategy when a candidate lattice point is found. For this purpose, the dynamic radius update strategy depending on the lattice point found as well as the lattice independent radius selection scheme are jointly exploited. As a result, while maintaining the effectiveness of the PTP-SD, further reduction of the computational complexity, in particular for high SNR regime, can be achieved. From simulations in multiple-input and multiple-output (MIMO) channels, it is shown that the proposed method provides a considerable improvement in complexity with near-ML performance.
Antifatigue effect of Gracilaria eucheumoides in mice

Gracilaria eucheumoides Linn (Gracilariaceae; G. eucheumoides) is abundant in dietary fiber, which aids the clearance of excess cholesterol from the blood and maintains stable blood glucose levels. The aim of the present study was to investigate the antifatigue effect of G. eucheumoides in mice and the physiological and molecular mechanisms underlying this effect. Mice were randomly divided into four groups and three of the groups were administered different doses of G. eucheumoides extract. A loaded swimming test demonstrated that the swimming times of the low-, medium- and high-dose groups were longer than those of the control group. Examinations revealed that the liver and muscle glycogen, lactate dehydrogenase and blood glucose concentration levels of the treatment groups were higher than those of the control group (P<0.05). However, this was not the case for lactic acid concentration (P>0.05). Quantitative polymerase chain reaction showed that the gene expression levels of glucose transport protein 4 and AMP-activated protein kinase in the medium-dose group exhibited the largest increases, compared with the other treatment groups, and were 3.0- and 1.8-fold higher than those in the control group, respectively. The results of the present study indicated that G. eucheumoides exerts an antifatigue effect on mice.
Strong consistency of the Sign-Perturbed Sums method

Sign-Perturbed Sums (SPS) is a recently developed non-asymptotic system identification algorithm that constructs confidence regions for parameters of dynamical systems. It works under mild statistical assumptions, such as symmetric and independent noise terms. The SPS confidence region includes the least-squares estimate, and, for any finite sample and user-chosen confidence probability, the constructed region contains the true system parameter with exactly the given probability. The main contribution in this paper is to prove that SPS is strongly consistent, in case of linear regression based models, in the sense that any false parameter will almost surely be excluded from the confidence region as the sample size tends to infinity. The asymptotic behavior of the confidence regions constructed by SPS is also illustrated by numerical experiments.
Load balancing in a changing world: dealing with heterogeneity and performance variability

Fully utilizing the power of modern heterogeneous systems requires judiciously dividing work across all of the available computational devices. Existing approaches for partitioning work require offline training and generate fixed partitions that fail to respond to fluctuations in device performance that occur at run time. We present a novel dynamic approach to work partitioning that requires no offline training and responds automatically to performance variability to provide consistently good performance. Using six diverse OpenCL#8482; applications, we demonstrate the effectiveness of our approach in scenarios both with and without run-time performance variability, as well as in more extreme scenarios in which one device is non-functional.
Robust Facial Feature Extraction Using Embedded Hidden Markov Model for Face Recognition under Large Pose Variation

We propose an algorithm for extracting facial features robustly from images for face recognition under large pose variation. Rectangular facial features are retrieved via the by-products of an embedded Hidden Markov Model (HMM) which decodes an observed face image into a state sequence. While an HMM is able to segment images into features at a fixed pose, multiple HMMs are trained for each individual to robustly extract features under large pose variation. Using the extracted features of each individual, appearance models based on subspaces are constructed for face identification and verification. The effectiveness of the proposed approach is validated through empirical studies against numerous methods using the CMU PIE database. Our experiments demonstrate that the proposed approach is able to extract facial features robustly, thereby rendering superior results in identification and superior performance in verification under large pose variation.
PowWow : Power Optimized Hardware/Software Framework for Wireless Motes

An energy-efficient platform for wireless sensor networks and its dedicated software framework are described and optimizations are proposed at both hardware and software level. The hardware is based on low cost and low power components linked in a multilayer architecture. Some processing, such as error correcting codes, are accelerated by a low power FPGA and the platform offers the possibility to dynamically adapt the voltage and the frequency of the processor. Finally the software system implementing the protocols stack has a very small memory foot print. Some parameters optimizations are then proposed at lower protocol layers to decrease the global energy consumption of the platform. The medium access protocol relies on an asynchronous rendez-vous scheme initiated by the receiver, and the wake-up interval can be tuned to increase the lifetime of the network. The influence of error correcting codes on the energy consumption is evaluated and some promising cooperative strategies, based on relay and distributed space-time codes are proposed.
No . 00-0803 Changes in Risk and Asset Prices

We examine asset prices in a representative-agent model of general equilibrium. Assuming only that individuals are risk averse, we determine conditions on the changes in asset risk that are both necessary and sufficient for the asset price to fall. We show that these conditions neither imply, nor are implied by the conditions for second-degree stochastic dominance. For example, if the payoff on an asset becomes riskier in the sense of second-degree stochastic dominance, the equilibrium price of the asset need not necessarily fall. We further demonstrate how our results can be imbedded into a market that is incomplete in the sense of containing an uninsurable background risk, such as a risk on labor income. We extend our model to show how a miscalibration of the asset risk can lead to a partial explanation of high equity premia (i.e., the "equity premium puzzle"). JEL classification: D51; G12
The Broader Context

Knowledge management is an emerging field focusing on assessing the creation, transfer, and utilization of knowledge to address specific challenges. Generally, knowledge management has described efforts within and between companies to consider knowledge as a manageable asset. In this paper, we suggest that occupational hygiene knowledge can be considered a manageable asset by businesses and that the entire field of occupational hygiene in the USA can be appraised in terms of knowledge management. The knowledge cycle creates a foundation for knowledge management. Knowledge creation (research, recognition and evaluation), transfer (distribution, dissemination and diffusion), and utilization (risk management and control) make up the key elements of the knowledge cycle. Defining and understanding the roles of knowledge cycle elements facilitate the application of knowledge management to problems, systems, and situations in individual companies and in the field of occupational hygiene in general. Examples of current, effective knowledge management practices within occupational hygiene in the USA are described, and recommendations for further utilization of knowledge management principles are also presented.
Human motion variation synthesis with multivariate Gaussian processes

Human motion variation synthesis is important for crowd simulation and interactive applications to enhance synthesis quality. In this paper, we propose a novel generative probabilistic model to synthesize variations of human motion. Our key idea is to model the conditional distribution of each joint via a multivariate Gaussian process model, namely semiparametric latent factor model (SLFM). SLFM can effectively model the correlations between degrees of freedom (DOFs) of joints rather than dealing with each DOF separately as implemented in existing methods. A detailed evaluation is performed to show that the proposed approach can effectively synthesize variations of different types of motions. Motions generated by our method show a richer variation compared with existing ones. Finally, our user study shows that the synthesized motion has a similar level of naturalness to captured human motions. Our method is best applied in computer games and animations to introduce motion variations. Copyright © 2014 John Wiley & Sons, Ltd.
A S-band colpitts VCO for fast hopping frequency synthesizer

This paper analyzed the basic theory of voltage controlled oscillator as well as the mathematical expression of hopping time in frequency synthesizer. The impaction of the oscillator gain of VCO on the hopping time is discussed consequently. Finally, a S-band colpitts VCO is designed and simulated in ADS and a novel type of mixed simulation method which can provide better accuracy is provided.
Integrated carbon nanotube-based sensor with CMOS processor for monitoring breath

Breath is one of vital functions for human. Development of an effective breath sensor to detect apnea is important issue in medical care. A new technology with integration of CMOS circuits and nano electromechanical system (NEMS) as breath sensor has been presented. Through a specifically treated procedure, multi-walled carbon nanotubes (MWCNTs) were immobilized on a silicon wafer. Techniques by photolithography and sputtering were then implemented on the MWCNT film to develop micro interdigitated electrodes as the basic structure of a breath sensor. The sensor was connected to a programmed Microchip operator to become a warning device for abnormal human breath. In this preliminary study with variable patterns of simulated tests to volunteers, MWCNT sensor combined with a CMOS processor could response rapidly and effectively as a detector for exhaled breath flow. Our results highlight that integrated CMOS circuits and NEMS could improve the pattern of respiratory care in the future.
On single sensor-based inertial navigation

In this paper, we compare two novel algorithms for pedestrian navigation based on signals collected by a single wearable Magnetic, Angular Rate, and Gravity (MARG) sensor. The two navigation algorithms, denoted as Enhanced Pedestrian Dead Reckoning (EPDR) and De-Drifted Propagation (DDP), require the placement of the MARG sensor on the foot or on the chest of the test subject, respectively. Different methods for gait characterization are compared, evaluating navigation dynamics by using data collected through an extensive experimental campaign. The main goal of this research is to investigate the peculiarities of different inertial navigation algorithms, in order to highlight the impact of the sensor's placement, together with inertial sensor issues. Considering a closed path (i.e., ending at the starting point), the relative distance error between the starting point and the final estimated position is about 2% of the total travelled distance for both DDP and EPDR navigation algorithms. On the other hand, the error between the initial heading angle and the final estimated one is approximately 10° for EPDR and 7° for DDP, respectively.
Secure communication in cooperative network with wireless information and power transfer

This paper considers the secure communication issue in an amplify-and-forward relaying cooperative network, in which the energy harvesting relay is powered by radio-frequency signals from the source. Based on the two different energy harvesting strategies, that is, power splitting-based relaying protocols and time switching-based relaying protocols, the authors formulate the problem for maximising the secrecy rate subject to the transmitted power constraint by taking into account the power splitting coefficient and time switching coefficient. The authors solve these problems by applying the semi-definite programming relaxation approach and 1D optimisation over the coefficients of energy harvesting protocols. The simulation results are presented to verify the effectiveness of these solutions proposed in this study.
Automatic generation of visual scenarios for spoken corpora acquisition

The paper describes a system, in JAVA, for written and visual scenario generation to collect speech corpora in the framework of a Tourism Information System. Methods and experimental results are also presented for evaluating the degree of understanding of the proposed scenarios. The corpus generated from visual scenarios appears to be much richer than the one generated from textual descriptions.
Novel GaN Power Transistor Substrate Connection to Minimize Common Mode Noise

Fast switching of GaN device would increase power converter common mode current $I_{cm}$ level. In this paper, it is proposed to connect substrate of the upper device in a half-bridge circuit to its drain terminal in order to decrease capacitive coupling between device switching node and ground plane so as to decrease $I_{cm}$ level. Device static and dynamic ON-state resistance and its inter-electrode capacitance are compared under different substrate connections, which shows that device static and dynamic characteristics do not noticeably degrade when connecting its substrate to drain terminal than conventional connection to its source terminal. Furthermore, $I_{cm}$ magnitude is reduced over the whole 150kHz to 30MHz conducted EMI frequency range, with 2dB-3dB reduced level between 150kHz to 3MHz and more than 5dB reduced level around 20MHz when device switches at 100V and 200V with switching frequency of 100kHz.
THE EFFECT OF INTERACTION WITH A THERAPY DOG ON COLLEGE STUDENT STRESS LEVELS AS MEASURED BY PHYSIOLOGICAL INDICATORS

by Kendra Rieger Thew, Ph.D. Washington State University July 2017 Chair: Phyllis Erdman Although animal-assisted activities have been shown to reduce stress, few studies have examined the stress reduction effects of therapy dogs on college student stress levels. Many college students experience increased stress levels due to the unique experience of college. These higher levels of stress can have negative consequences such as increased drinking, dysfunctional coping mechanisms, and more. This creates a need for alternative methods of stress reduction. Animal assisted activities (AAA) is a growing area of interest that has many benefits including stress reduction. However, few studies provide empirical evidence for stress reduction based on physiological measures. Of the studies that have incorporated physiological measures, results have proved to be inconsistent. Furthermore, even though stress relieving programs are increasing in popularity on college campuses, few studies have examined the stress reduction effects of therapy dogs on college student stress levels. College students were recruited and randomly assigned to an experimental condition (with a therapy dog and human handler present) or a control condition (with no therapy dog or human handler present). Participants were outfitted with equipment to measure systolic blood pressure, diastolic blood pressure, and skin temperature. They watched a 10 minute video and were asked quiz questions about the content of
The relationship between perseverative cognitions and mental health and physical health complaints among college students

Abstract College students often experience health problems, but approaches are needed to determine those that are most vulnerable. This study examined whether perseverative cognitions (PCs) represent a common risk factor for poor health. Students (n = 489) completed measures of PCs, posttraumatic stress disorder (PTSD) symptomatology, general mental health, and physical health complaints. Regressions indicated that PCs were associated with higher levels of PTSD symptomatology, poor mental health, and physical health complaints. Structural equation modeling analyses suggested that PTSD symptoms explain, in part, the association between PCs and physical health complaints. Results are discussed in terms of PCs as a risk stratifying factor.
Small Malignant Hepatic Tumor Detection in Gadolinium- and Ferucarbotran-Enhanced Magnetic Resonance Imaging: does Combining Ferucarbotran-Enhanced T2*-Weighted Gradient Echo and T2-Weighted Turbo Spin Echo Images have Additive Efficacy?

Objective To determine if a combination of ferucarbotran-enhanced T2*weighted-gradient echo (T2*W-GRE) and T2-weighted turbo spin echo (T2W-TSE) images in gadolinium- and ferucarbotran-enhanced MRI has additive efficacy compared to each image alone for detecting small (≤ 2.0 cm) hepatocellular carcinoma (HCC) lesions in a group of cirrhotic patients and metastases in a group of non-cirrhotic patients. Materials and Methods Two readers retrospectively analyzed gadolinium- and ferucarbotran-enhanced T2*W-GRE, T2W-TSE, and combined T2*W-GRE/T2W-TSE images of 119 patients with 157 HCCs and 32 patients with 98 metastases. The diagnostic accuracy and sensitivity for each image set and the combined set were evaluated using the alternative-free response receiver operating characteristic method. Results The mean area under the curve value of the combined set (0.966) tended to be better than that for each individual image set (T2W-TSE [0.910], T2*W-GRE [0.892]). Sensitivities in the combined set were higher than those in each individual image set for detecting HCC (mean, 93.0% versus 81.6% and 86.7%, respectively, p < 0.01). Sensitivities in the combined set and the T2W-TSE set were the same for detecting metastases, and both were higher than the sensitivity seen in the T2*W-GRE set (mean, 97.5% versus 85.2%, p < 0.01). Conclusion Combining ferucarbotran-enhanced T2*W-GRE and T2W-TSE has additive efficacy for detecting HCC in cirrhotic patients, but T2W-TSE is preferred for detecting metastases in non-cirrhotic patients.
An Eye-Tracking Study of Query Reformulation

Information about a user's domain knowledge and interest can be important signals for many information retrieval tasks such as query suggestion or result ranking. State-of-the-art user models rely on coarse-grained representations of the user's previous knowledge about a topic or domain. In this paper, we study query refinement using eye-tracking in order to gain precise and detailed insight into which terms the user was exposed to in a search session and which ones they showed a particular interest in. We measure fixations on the term level, allowing for a detailed model of user attention. To allow for a wide-spread exploitation of our findings, we generalize from the restrictive eye-gaze tracking to using more accessible signals: mouse cursor traces. Based on the public API of a popular search engine, we demonstrate how query suggestion candidates can be ranked according to traces of user attention and interest, resulting in significantly better performance than achieved by an attention-oblivious industry solution. Our experiments suggest that modelling term-level user attention can be achieved with great reliability and holds significant potential for supporting a range of traditional IR tasks.
Mathematical formulation of the relationship between photosynthesis and light for phytoplankton

Eight different mathematical formulations of the photosynthesis—light curve for phytoplankton (up to and including light saturation) were recast in terms of the same two parameters: the initial slope α, and the assimilation number PmB. Each equation was tested for its ability to describe empirical data from natural populations of marine phytoplankton: the results of 188 light-saturation experiments at three coastal locations in Nova Scotia over a 2-year period. The most consistently useful mathematical representation of the data was found to be the hyperbolic tangent function.
Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting

Psychophysiological research integrating heart rate variability (HRV) has increased during the last two decades, particularly given the fact that HRV is able to index cardiac vagal tone. Cardiac vagal tone, which represents the contribution of the parasympathetic nervous system to cardiac regulation, is acknowledged to be linked with many phenomena relevant for psychophysiological research, including self-regulation at the cognitive, emotional, social, and health levels. The ease of HRV collection and measurement coupled with the fact it is relatively affordable, non-invasive and pain free makes it widely accessible to many researchers. This ease of access should not obscure the difficulty of interpretation of HRV findings that can be easily misconstrued, however, this can be controlled to some extent through correct methodological processes. Standards of measurement were developed two decades ago by a Task Force within HRV research, and recent reviews updated several aspects of the Task Force paper. However, many methodological aspects related to HRV in psychophysiological research have to be considered if one aims to be able to draw sound conclusions, which makes it difficult to interpret findings and to compare results across laboratories. Those methodological issues have mainly been discussed in separate outlets, making difficult to get a grasp on them, and thus this paper aims to address this issue. It will help to provide psychophysiological researchers with recommendations and practical advice concerning experimental designs, data analysis, and data reporting. This will ensure that researchers starting a project with HRV and cardiac vagal tone are well informed regarding methodological considerations in order for their findings to contribute to knowledge advancement in their field.