Miracle-dz/UniFAR-FTUs huggingface dataset:
Perceptual Sensitivity and Response to Strong Stimuli Are Related

To shed new light on the long-standing debate about the (in)dependence of sensitivity to weak stimuli and overreactivity to strong stimuli, we examined the relation between these tendencies within the neurobehavioral framework of the Predictive and Reactive Control Systems (PARCS) theory (Tops et al., 2010, 2014). Whereas previous studies only considered overreactivity in terms of the individual tendency to experience unpleasant affect (punishment reactivity) resulting from strong sensory stimulation, we also took the individual tendency to experience pleasant affect (reward reactivity) resulting from strong sensory stimulation into account. According to PARCS theory, these temperamental tendencies overlap in terms of high reactivity toward stimulation, but oppose each other in terms of the response orientation (approach or avoid). PARCS theory predicts that both types of reactivity to strong stimuli relate to sensitivity to weak stimuli, but that these relationships are suppressed due to the opposing relationship between reward and punishment reactivity. We measured punishment and reward reactivity to strong stimuli and sensitivity to weak stimuli using scales from the Adult Temperament Questionnaire (Evans and Rothbart, 2007). Sensitivity was also measured more objectively using the masked auditory threshold. We found that sensitivity to weak stimuli (both self-reported and objectively assessed) was positively associated with self-reported punishment and reward reactivity to strong stimuli, but only when these reactivity measures were controlled for each other, implicating a mutual suppression effect. These results are in line with PARCS theory and suggest that sensitivity to weak stimuli and overreactivity are dependent, but this dependency is likely to be obscured if punishment and reward reactivity are not both taken into account.
Coordinate Mapping Between an Acoustic and Visual Sensor Network in the Shape Domain for a Joint Self-Calibrating Speaker Tracking

"Several self-localization algorithms have been proposed, that determine the positions of either acoustic or visual sensors autonomously. Usually these positions are given in a modality specific coordinate system, with an unknown rotation, translation and scale between the different systems. For a joint audiovisual tracking, where the different modalities support each other, the two modalities need to be mapped into a common coordinate system. In this paper we propose to estimate this mapping based on audiovisual correlates, i.e., a speaker that can be localized by both, a microphone and a camera network separately. The voice is tracked by a microphone network, which had to be calibrated by a self-localization algorithm at first, and the head is tracked by a calibrated camera network. Unlike existing Singular Value Decomposition based approaches to estimate the coordinate system mapping, we propose to perform an estimation in the shape domain, which turns out to be computationally more efficient. Simulations of the self-localization of an acoustic sensor network and a following coordinate mapping for a joint speaker localization showed a significant improvement of the localization performance, since the modalities were able to support each other. "
Integrating Metatheory to Enhance Qualitative Interviewing: A Safety Campaign Exemplar

This article examines the ways in which integrating a metatheory to guide qualitative interviews supports health theory and the research methodology of interviewing. This study applied Harm Reduction Theory (HRT) as a metatheory to the Reconceptualized Health Belief Model (RHBM) in targeting motorcyclists to practice safety behaviors. After integrating the metatheory with a health behavior theory to develop research questions and frame the interview guide, we recruited and interviewed 37 at-risk motorcyclists. The process of interviewing participants and the results of the study support the integration of harm reduction metatheory to enhance interview methodology as a way to effectively engage participants by building rapport, encouraging participants to apply theory, and empowering them to be open and honest in their responses. This research process highlights ways in which incorporating a metatheory to guide theory diverges from the more traditional, theory-driven approach to interviewing.
Mapping Embedded Systems onto NoCs - The Traffic Effect on Dynamic Energy Estimation

This work addresses the problem of application mapping in networks-on-chip (NoCs). It explores the importance of characterizing network traffic to effectively predict NoC energy consumption. Traffic is seen as an important factor affecting the problem of mapping applications into NoCs having as goal to minimize the total dynamic energy consumption of a complex system-on-a-chip (SoC). Experiments showed that failing to consider the bit transitions influence on traffic inevitably leads to an energy estimation error. This error is proportional to the amount of bit transitions in transmitted packets. In applications that present a large number of packets exchange, the error is propagated, significantly affecting the mapping results. This paper proposes a high-level application model that captures the traffic effect and uses it to describe the behavior of applications. In order to evaluate the quality of the proposed model, a set of embedded systems were described using both, a previously proposed model (that does not capture the traffic effect), and the model proposed here. Comparing the resulting mappings, those derived from the proposed model showed improvements in energy savings with regard to the other model for all experiments
Vascular Patterns in Glioblastoma Influence Clinical Outcome and Associate with Variable Expression of Angiogenic Proteins: Evidence for Distinct Angiogenic Subtypes

No data exist on angiogenic patterns and their prognostic impact in human glioblastoma. Such data are relevant for translation of antiangiogenic therapies into clinical applications. Using immunohistochemistry for CD34, we assessed vascular patterns in 114 primary glioblastomas. Vascular patterns comprised unevenly distributed glomeruloid/garland‐like/clustered bizarre vascular formations and evenly distributed delicate capillary‐like microvessels (“classic” vascular pattern). The combination of low content of bizarre vascular formations and prominent classic vascular pattern (n=29) was an independent factor for longer survival (p= 0.006, Cox regression), as well as postoperative high Karnofsky performance status (p=0.005). In patients with a prominent classic vascular pattern, there was no difference of MIB1 labeling index whereas microvessel density and apoptotic index (TUNEL) were significantly higher as compared to all other patients (p<0.05). In addition, diffuse expression of hypoxia‐inducible factor (HIF)‐1α and strong expression of vascular endothelial growth factor were more common (p<0.05, Chi‐square test). FISH revealed loss of chromosomes 1p and 19q only in 1/7 long‐time survivors with classic pattern. We conclude that vascular patterns in primary glioblastoma influence clinical outcome and associate with variable expression of angiogenic proteins. Our findings denote for the first time distinct angiogenic subtypes of human glioblastoma which may prove relevant for anti‐angiogenic therapy approaches.
Semi-chronic chamber system for simultaneous subdural electrocorticography, local field potentials, and spike recordings

The brain operates on many different scales, from individual neurons to interacting cortical areas. Similarly, electrophysiology can monitor neural activity at a variety of spatial resolutions. Yet the majority of electrophysiology studies focus on a single scale of measurements. Simultaneously monitoring neural activity at multiple spatial scales will be critical for better understanding neural processing and developing neuroprosthetic applications. Here, we address the technical challenge of integrating multiple recording modalities into a chronic recording system. We developed a semi-chronic chamber-based system for non-human primates to simultaneously record subdural micro-electrocorticography (μECoG), local field potentials (LFPs) and action potentials in the same tissue volume. The system combines subdural μECoG array recordings with a microdrive and uses a chamber system and artificial duras to align each component. We present the system design and validation of subdural μECoG recordings using artificial duras. Acute recordings from one non-human primate subject are shown to validate the technique.
Are We Providing Resources That Stimulate Engagement, Active Learning and Academic Achievement? A Case Study of On–campus Nursing Students.

Pathophysiology and pharmacology subjects are keystone to the pre-registration Bachelor of Nursing Science degree at James Cook University. These disciplines are typically considered by nursing students to be difficult to understand, and academic achievement in these subjects is often lower than in other subjects within the Bachelor of Nursing Science program. On-campus and off–campus students are provided with a range of resources to aid learning. The purpose of this study was to investigate the engagement of on–campus students with the resources provided for learning pathophysiology and pharmacology, to determine which resources promoted active learning, and to use this information for comparison with the responses of the off–campus cohort. Students were invited to complete a questionnaire which collected information about student demographics, interactions with learning resources, and subject grades. On–campus and off–campus cohorts reported different patterns of engagement with learning resources, however both the total amount of engagement and the total amount of active learning, showed positive relationships with academic achievement. Delivery of key pathophysiology and pharmacology concepts through formats in which students engage with more often and more actively may be strategic in promoting academic achievement and enjoyment in learning pathophysiology and pharmacology.
Short-time instantaneous frequency and bandwidth features for speech recognition

In this paper, we investigate the performance of modulation related features and normalized spectral moments for automatic speech recognition. We focus on the short-time averages of the amplitude weighted instantaneous frequencies and bandwidths, computed at each subband of a mel-spaced filterbank. Similar features have been proposed in previous studies, and have been successfully combined with MFCCs for speech and speaker recognition. Our goal is to investigate the stand-alone performance of these features. First, it is experimentally shown that the proposed features are only moderately correlated in the frequency domain, and, unlike MFCCs, they do not require a transformation to the cepstral domain. Next, the filterbank parameters (number of filters and filter overlap) are investigated for the proposed features and compared with those of MFCCs. Results show that frequency related features perform at least as well as MFCCs for clean conditions, and yield superior results for noisy conditions; up to 50% relative error rate reduction for the AURORA3 Spanish task.
Improved SAI method using non-local spatial constraint for image interpolation

This paper proposes an improved image interpolation method based on the soft-decision adaptive interpolation (SAI) algorithm. Natural images often contain repeatable patterns and structures throughout the image, which is called non-local property. We can use this non-local strategy to improve the interpolation quality by better estimating the model parameters and Lagrangian multiplier. There are two steps in our method. In the first step, similar patches of the given block are found in the initialized high resolution image, and the model parameters can be determined properly using the expanded piecewise auto regression (PAR) model and non-local spatial constraint. In the second step, the self-similarity of patches across the high and low resolution images is exploited to solve the Lagrangian multiplier λ, thus to make the data estimation robust. Experiments indicate that the improved method can achieve good results both subjectively and objectively.
Three-layered draw-attention model for humanoid robots with gestures and verbal cues

When we talk about objects in an environment, we indicate to a listener which object is currently under consideration by using pointing gesture and such reference terms as "this" and "that". Such reference terms play an important role in human interaction by quickly informing the listener of an indicated object's location. In this research, we propose a three-layered draw-attention model for humanoid robots with gestures and verbal cues. Our proposed three-layered model consists of three sub models: reference term model (RTM), limit distance model (LDM) and object property model (OPM). RTM decides an appropriate reference term using functions constructed by an analysis of human behavior. LDM decides whether to use the object's property with a reference term. OPM decides the appropriate property for indicating the object by comparing object properties with each other. We developed an attention drawing system in a communication robot named "Robovie" based on the three layered model. We confirmed its effectiveness through the experiments.
SwordFight: enabling a new class of phone-to-phone action games on commodity phones

Mobile gaming is a big driver of app marketplaces. However, few mobile games deliver truly distinctive gameplay experiences for ad hoc collocated users. As an example of such an experience, consider a sword fight dual between two users facing each other where each user's phone simulates a sword. With phone in hand, the users' thrusts and blocks translate to attacks and counterattacks in the game. Such Phone-to-Phone Mobile Motion Games (MMG) represent interesting and novel gameplay for ad hoc users in the same location. One enabler for an MMG game like sword fight is continuous, accurate distance ranging. Existing ranging schemes cannot meet the stringent requirements of MMG games: speed, accuracy and noise robustness. In this work, we design FAR, a new ranging scheme that can localize at 12Hz with 2cm median error while withstanding up to 0dB noise, multipath and Doppler effect issues. Our implementation runs on commodity smartphones and does not require any external infrastructure. Moreover, distance measurement accuracy is comparable to that of Kinect, a fixed-infrastructure motion capture system. Evaluation on users playing two prototype games indicate that FAR can fully support dynamic game motion in real-time.
2016 Ieee International Conference on Big Data (big Data) Research on the Big Data System of Massive Open Online Course

—With no limit on time and location [1], the number of users attracted by massive open online course (MOOC) has increased rapidly, and many platforms have been built to provide a variety of courses. All of these trigger an explosive growth in data volume. As we known, people have met big data in many areas and proposed many techniques and methods to deal with them. However, people still have no sense of the data system in MOOC. How to dig out valuable information from its big data to benefit all stockholders is an instant challenge. This paper has an insight into the data system in MOOC and proposes Data Ming goals and methods. At last, the paper will introduce the computing platform and CNMOOC as a case study.
Breast cancer quality of life evaluation in Mexican Women at La Raza Hospital, Mexico City: A preliminary approach

Breast cancer (BC) is the second leading cause of death among Mexican women over 40 years of age. This study aimed to identify and examine the effects of cancer stage and surgical treatment on the quality of life (QOL) of Mexican women with early stage breast cancer (ESBC) treated with either modified radical mastectomy (MRM) or breast conservative surgery (BCS), plus adjuvant chemotherapy. The QLQ-C30 and QLQ BR-23 questionnaires were used to assess QOL. Sociodemographic characteristics and clinical factors of 102 women with early BC were also evaluated; analysis of variance (ANOVA) was performed and a statistical significance of p < 0.05 was assumed. Most women were of reproductive age. Meaningful differences in QOL as a result of surgical treatment, in women receiving BCS compared with those receiving MRM, were limited to body image. We conclude that MRM and BCS are essentially equivalent choices in terms of QOL, with the exception of the impact on body image. In general, women who received BCS had a better perceived QOL.
Optimizing time series discretization for knowledge discovery

Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal order of values. This often leads to symbols that do not correspond to states of the process generating the time series and cannot be interpreted meaningfully. We propose a new method for meaningful unsupervised discretization of numeric time series called Persist. The algorithm is based on the Kullback-Leibler divergence between the marginal and the self-transition probability distributions of the discretization symbols. Its performance is evaluated on both artificial and real life data in comparison to the most common discretization methods. Persist achieves significantly higher accuracy than existing static methods and is robust against noise. It also outperforms Hidden Markov Models for all but very simple cases.
Interaction between radiation and drug damage in mammalian cells. I. Delayed expression of actinomycin D/x-ray effects in exponential and plateau phase cells.

The survival characteristics of V79 Chinese hamster cells exposed to either X-radiation or actinomycin-D and subsequently treated with the other modality were studied. Exponentially growing cells were exposed to either 820 R, 50 kVp X rays or 3.0 μg/ml AMD for 30 min and the survivors were exposed to graded doses of the other agent 2, 3, and 7 days afterward. The previously irradiated cells did not differ in their response to subsequent AMD, whereas the cells which had survived AMD demonstrated a decrease in extrapolation number and $\tilde{D}_{Q}$ when exposed to X rays as compared to cells not previously treated with AMD. The X-ray two-dose response was studied in cells exposed to 3.0 μg/ml 3 days before. The AMD treated cells had a lower maximum recovery ratio than controls and subsequent survival with time between doses was lower than in controls. Similar experiments were done with stationary (plateau phase) V79 cells. The response of stationary cells to AMD after either similar d.
Automated assessment of cognitive health using smart home technologies.

BACKGROUND The goal of this work is to develop intelligent systems to monitor the wellbeing of individuals in their home environments. OBJECTIVE This paper introduces a machine learning-based method to automatically predict activity quality in smart homes and automatically assess cognitive health based on activity quality. METHODS This paper describes an automated framework to extract set of features from smart home sensors data that reflects the activity performance or ability of an individual to complete an activity which can be input to machine learning algorithms. Output from learning algorithms including principal component analysis, support vector machine, and logistic regression algorithms are used to quantify activity quality for a complex set of smart home activities and predict cognitive health of participants. RESULTS Smart home activity data was gathered from volunteer participants (n=263) who performed a complex set of activities in our smart home testbed. We compare our automated activity quality prediction and cognitive health prediction with direct observation scores and health assessment obtained from neuropsychologists. With all samples included, we obtained statistically significant correlation (r=0.54) between direct observation scores and predicted activity quality. Similarly, using a support vector machine classifier, we obtained reasonable classification accuracy (area under the ROC curve=0.80, g-mean=0.73) in classifying participants into two different cognitive classes, dementia and cognitive healthy. CONCLUSIONS The results suggest that it is possible to automatically quantify the task quality of smart home activities and perform limited assessment of the cognitive health of individual if smart home activities are properly chosen and learning algorithms are appropriately trained.
Query flocks: a generalization of association-rule mining

Association-rule mining has proved a highly successful technique for extracting useful information from very large databases. This success is attributed not only to the appropriateness of the objectives, but to the fact that a number of new query-optimization ideas, such as the “a-priori” trick, make association-rule mining run much faster than might be expected. In this paper we see that the same tricks can be extended to a much more general context, allowing efficient mining of very large databases for many different kinds of patterns. The general idea, called “query flocks,” is a generate-and-test model for data-mining problems. We show how the idea can be used either in a general-purpose mining system or in a next generation of conventional query optimizers.
Coming together: the ATS/ERS consensus on clinical pulmonary function testing

Since 1979, guidelines for standardising pulmonary function tests have been published and updated by both the American Thoracic Society (ATS) 1–6 and the European Respiratory Society (ERS) 7–9. In addition, several joint ATS/ERS workshops on pulmonary function testing have been held and the resulting reports published 10, 11. In 1995, European scientists participated in the ATS updates of standards for spirometry and single-breath carbon monoxide diffusing capacity of the lung ( D L,CO), but no joint statement has been published by the two societies. Although generally concordant, the spirometry and D L,CO guidelines published separately by the ATS and the ERS differed in some aspects that were of appreciable importance. Official guidelines for the measurement of lung volumes were made available by the ERS 7, 10, but not the ATS. In recent years, global initiatives were undertaken for the diagnosis and treatment of pulmonary diseases, and the worldwide market for instruments to test lung function widened considerably. This increased the pressure for more uniform pulmonary function testing across the world, and prompted the ATS and the ERS to appoint a joint Task Force to provide new combined standards for clinical pulmonary function testing, with the hope that they will be accepted by other respiratory societies. A new Task Force on pulmonary function testing, implemented by the Forum of International Respiratory Societies (FIRS), has recently started its work based on the ATS/ERS documents. Our Task Force consisted of 19 scientists with recognised expertise in pulmonary function testing. The group worked on a “one-draft” system, in which each of five sections was assigned to a small subgroup and eventually discussed by the whole committee. There …