LLukas22/scidocs huggingface dataset:
Topic-Aware Deep Compositional Models for Sentence Classification

In recent years, deep compositional models have emerged as a popular technique for representation learning of sentence in computational linguistic and natural language processing. These models normally train various forms of neural networks on top of pretrained word embeddings using a task-specific corpus. However, most of these works neglect the multisense nature of words in the pretrained word embeddings. In this paper we introduce topic models to enrich the word embeddings for multisenses of words. The integration of the topic model with various semantic compositional processes leads to topic-aware convolutional neural network and topic-aware long short term memory networks. Different from previous multisense word embeddings models that assign multiple independent and sense-specific embeddings to each word, our proposed models are lightweight and have flexible frameworks that regard word sense as the composition of two parts: a general sense derived from a large corpus and a topic-specific sense derived from a task-specific corpus. In addition, our proposed models focus on semantic composition instead of word understanding. With the help of topic models, we can integrate the topic-specific sense at word-level before the composition and sentence-level after the composition. Comprehensive experiments on five public sentence classification datasets are conducted and the results show that our proposed topic-aware deep compositional models produce competitive or better performance than other text representation learning methods.
The effects of cold, touch, and chemical stimulation of the anterior faucial pillar on human swallowing

Cold stimulation of the oropharyngeal mucosa, including the faucial pillar region, is used as a specific technique for the treatment of swallowing disorders. The physiological mechanisms underpinning this clinical technique are unclear. Thermal (cold), chemical (saline, glucose and water), mechanical (light touch) and feigned stimulation of the faucial pillar were assessed for their effects on the latency to swallow and the repetitive frequency of swallowing. There was no significant difference between these variables following light stimulation of the faucial pillar with a metal probe warmed to body temperature compared with feigned stimulation. However, cold touch stimulation evoked a significant increase in swallowing latency and repetitive frequency compared to feigned stimulation. The results suggest the existence of thermo-sensitive receptors in the faucial pillars that evoke swallowing when stimulated by cold touch. The clinical and physiological importance of these findings are discussed.
Multiple autonomic and repolarization investigation of sudden cardiac death in dilated cardiomyopathy and controls.

BACKGROUND
Prophylactic defibrillator implantation is recommended in dilated, nonischemic heart disease and left ventricular ejection fraction of ≤0.30 to 0.35. Noninvasive testing should improve accuracy in decision making of prophylactic defibrillator implantation.


METHODS AND RESULTS
We enrolled 60 patients (median age, 57 years) with dilated cardiomyopathy and left ventricular ejection fraction ≤0.50, and 30 control subjects (median age, 59 years) with left ventricular ejection fraction >0.50. The protocol included an initial assessment, a second assessment after 3 years, and a final follow-up: pharmacological baroreflex testing (baroreceptor reflex sensitivity), short-term spectral analysis of heart rate variability (low frequency/high frequency), and long-term time domain analysis (SD of all normal-to-normal R-R intervals), exercise microvolt T wave alternans, and signal-averaged ECG, and corrected QT-time. The median follow-up was 7 years. End points were cardiac death, resuscitated cardiac arrest, and arrhythmic death. Cardiac death was observed in 21 patients. Resuscitated cardiac arrest and arrhythmic death caused by ventricular tachyarrhythmias ≥240 per minute was observed in 7 and 10 patients, respectively. In the single time point analysis, microvolt T wave alternans, baroreceptor reflex sensitivity, and SD of all normal-to-normal R-R intervals at initial testing added significant information regarding cardiac death. Microvolt T wave alternans added information on resuscitated cardiac arrest or arrhythmic death at multiple time points (P<0.001). False-negative microvolt T wave alternans results were seen in 8% of patients.


CONCLUSIONS
Noninvasive testing and left ventricular ejection fraction could not reliably identify patients with dilated cardiomyopathy at risk of fatal ventricular tachyarrhythmias. Therefore, the strategy to confine prophylactic implantable cardioverter-defibrillator implantation to patients with dilated cardiomyopathy and severely reduced LV function should be reconsidered.
Impact of cultural background on fundamental movement skill and its correlates.

Children's fundamental movement skill levels (FMS) predict moderate-to-vigorous physical activity (MVPA). Asian children have been reported as less active than English-Europeans, possibly due to poorer skills. This study compared the FMS of children from Culturally and Linguistically Diverse (CALD) backgrounds and examined FMS correlates. A total of 261 children (122 males) aged 9-to-11 years were divided based on language spoken at home: English-European (n = 105) and Asian (n = 156). Height, mass, FMS (Test of Gross Motor Development-2), MVPA (accelerometer) and cardio-respiratory fitness (20m multistage shuttle run) were directly measured. Sex, age, language and perceived sport competence (CY-PSPP) were self-reported. Independent sample t-tests assessed age, BMI, FMS and perception by CALD group. Linear mixed models examined FMS correlates. Asian-speaking children had lower object control skill (35.5 v 37.2; CI [0.17, 3.18]; p < 0.03) compared to English-European- children, but no between-group differences in locomotor skills were observed. Fitness, physical activity and sport competence perception were positively associated with object control, yet adjusting for these variables (and age and BMI) did not remove the CALD effect (B = -2.02, SE = 0.69, p = 0.004). Cultural factors may affect object control competence in Asian-Australian children.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Few prior works study deep learning on point sets. PointNet [20] is a pioneer in this direction. However, by design PointNet does not capture local structures induced by the metric space points live in, limiting its ability to recognize fine-grained patterns and generalizability to complex scenes. In this work, we introduce a hierarchical neural network that applies PointNet recursively on a nested partitioning of the input point set. By exploiting metric space distances, our network is able to learn local features with increasing contextual scales. With further observation that point sets are usually sampled with varying densities, which results in greatly decreased performance for networks trained on uniform densities, we propose novel set learning layers to adaptively combine features from multiple scales. Experiments show that our network called PointNet++ is able to learn deep point set features efficiently and robustly. In particular, results significantly better than state-of-the-art have been obtained on challenging benchmarks of 3D point clouds.
Pain intensity variability and its relationship with quality of life in youths with juvenile idiopathic arthritis.

OBJECTIVE
To describe variability of pain intensity experienced by youths with juvenile idiopathic arthritis (JIA) and examine factors related to within-day patterns of pain and the relationship between magnitude of pain variability and quality of life.


METHODS
Pain intensity was self-reported on a visual analog scale (VAS; range 0-100) by 112 youths with JIA ages 8-18 years using electronic diaries 3 times per day for 7 days. Average absolute change in pain (AAC) was computed as a measure of the magnitude of pain variability for each participant. Logistic regression was used to examine the relationship between demographic and disease characteristics and the probability of having high pain variability (AAC ≥10 VAS units). Linear regression was used to examine the relationship between quality of life (assessed by the Pediatric Quality of Life Inventory) and AAC. The generalized estimating equations approach was used to examine the relationship between the time of day and pain intensity.


RESULTS
The mean ± SD AAC was 15.6 ± 10.5. The majority of youths (65%) had high AAC (≥10 VAS units). Disease severity predicted high pain variability (β = 0.02, P = 0.044). Higher AAC predicted lower quality of life (adjusted R(2) = 0.194, β = -0.59, P = 0.003). Within-day patterns of pain intensity varied by JIA subtype and sex.


CONCLUSION
This study characterized the pain intensity variability experienced by youths with JIA. Pain variability throughout the day was common, varied by JIA subtype and sex, and was related to quality of life. These findings have implications for future pain research, patient education, and development of clinical interventions for this population.
A System to Filter Unwanted Messages from OSN User Walls

One fundamental issue in today's Online Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning-based soft classifier automatically labeling messages in support of content-based filtering.
Temporal Description Logics: A Survey

We survey temporal description logics that are based on standard temporal logics such as LTL and CTL. In particular, we concentrate on the computational complexity of the satisfiability problem and algorithms for deciding it.
Roux-en-Y gastric bypass and calorie restriction induce comparable time-dependent effects on thyroid hormone function tests in obese female subjects.

OBJECTIVE
Obesity and weight loss influence thyroid hormone physiology. The effects of weight loss by calorie restriction vs Roux-en-Y gastric bypass (RYGB) in obese subjects have not been studied in parallel. We hypothesized that differences in transient systemic inflammation and catabolic state between the intervention types could lead to differential effects on thyroid hormone physiology.


DESIGN AND METHODS
We recruited 12 lean and 27 obese females with normal fasting glucose (normal glucose tolerant (NGT)) and 27 obese females with type 2 diabetes mellitus (T2DM) for this study. Weight loss was achieved by restrictive treatment (gastric banding or high-protein-low-calorie diet) or by RYGB. Fasting serum leptin, TSH, triiodothyronine (T₃), reverse T₃ (rT₃), and free thyroxine (fT₄) concentrations were measured at baseline and 3 weeks and 3 months after the start of the interventions.


RESULTS
Obesity was associated with higher TSH, T₃, and rT₃ levels and normal fT₄ levels in all the subjects when compared with the controls. After 3 weeks, calorie restriction and RYGB induced a decline in TSH levels and a rise in rT₃ and fT₄ levels. The increase in rT₃ levels correlated with serum interleukin 8 (IL8) and IL6 levels. After 3 months, fT₄ and rT₃ levels returned to baseline levels, whereas TSH and T₃ levels were persistently decreased when compared with baseline levels. No differences in the effects on thyroid hormone parameters between the interventions or between NGT and T2DM subjects were observed at any time point.


CONCLUSIONS
In summary, weight loss directly influences thyroid hormone regulation, independently of the weight loss strategy used. The effects may be explained by a combination of decreased leptin levels and transient changes in peripheral thyroid hormone metabolism.
Design of Compact Dual-Band Bandpass Filter Using λ/4 Resonators

In this paper, a simple and effective method using two sets of lambda/4 resonators for designing dual-band filter has been investigated, and a practical filter has been fabricated, which provides two passbands at 2.4 and 5.2 GHz for WLAN application. The dual-passband characteristics are generated by adjusting the physical dimension of the top and bottom lambda/4 resonators. The bandwidth of each passband could be controlled independently by tuning the coupling gap. The measured insertion losses are 1.1 dB and 1.8 dB and the return losses are 24 dB and 20 dB at 2.4 and 5.2 GHz, respectively.
Embedded Software: Facts, Figures, and Future

Due to the complex system context of embedded-software applications, defects can cause life-threatening situations, delays can create huge costs, and insufficient productivity can impact entire economies. Providing better estimates, setting objectives, and identifying critical hot spots in embedded-software engineering requires adequate benchmarking data.
Playable Experiences at AIIDE 2015

This paper describes entries to the third Playable Experiences track to be held at the AIIDE conference. We discuss the five entries accepted to the track for 2015, as well as the ongoing development of the track as part
Dynamic localization control for mobile sensor networks

Localization is a fundamental operation in mobile and self-configuring networks such as sensor networks and mobile ad hoc networks. For example, sensor location is often critical for data interpretation. Existing research focuses on localization mechanisms: algorithms and infrastructure designed to allow the sensors to determine their location. In a mobile environment, the underlying localization mechanism must be invoked repeatedly to maintain accurate location information. We propose and investigate adaptive and predictive protocols that control the frequency of localization based on sensor mobility behavior to reduce the energy requirements for localization while bounding the localization error. In addition, we evaluate the energy-accuracy tradeoffs. Our results indicate that the proposed protocols reduce the localization energy significantly without sacrificing accuracy.
Design approaches for bodyworn RFID tags

Bodyworn tags are a challenging application for radio frequency identification (RFID) systems. The importance of this application will increase in the future due to emerging novel wireless identification and sensor systems. In this paper, a literature survey of wearable RFID tag antennas is presented. One-layer and multilayer tags are compared. The body effect on antenna parameters is analysed. Based on the findings, guidelines for wearable tag antenna design are given. As an example of a bodyworn tag, a meandered dipole is presented.
Modeling and forecasting pelagic fish production using univariate and multivariate ARIMA models

Univariate and multivariate autoregressive integrated moving average (ARIMA) models were used to model and forecast the monthly pelagic production of fish species in the Mediterranean Sea during 1990–2005. Autocorrelation (AC) and partial autocorrelation (PAC) functions were estimated, which led to the identification and construction of seasonal ARIMA models, suitable in explaining the time series and forecasting the future catch per unit of effort (CPUE) values. Univariate and multivariate ARIMA models satisfactorily predicted the total pelagic fish production and the production of anchovy, sardine, and horse mackerel. The univariate ARIMA models demonstrated a good perpormance in terms of explained variability and predicting power. The current findings revealed a strong autoregressive character providing relatively high R 2 and satisfactory forecasts that were close to the recorded CPUE values. The present results also indicated that the multivariate ARIMA outperformed the univariate ARIMA models in terms of fitting accuracy. The opposite was evidenced when testing the forecasting accuracy of the two methods, where the univariate ARIMA models overall performed better than the multivariate models. The observed seasonal pattern in the monthly production series was attributed to the intrinsic nature of the pelagic fishery. As anchovy, sardine, and horse mackerel represent main target species in the Mediterranean pelagic fishery, the findings of the present study provided direct support for the potential use of accurate forecasts in decision making and fisheries management in the Mediterranean Sea.
Effect of 12-week administration of 20-mg long-acting methylphenidate on Glu/Cr, NAA/Cr, Cho/Cr, and mI/Cr ratios in the prefrontal cortices of school-age children in Indonesia: a study using 1H magnetic resonance spectroscopy (MRS).

OBJECTIVES
Recent studies on the neurobiology of attention-deficit/hyperactivity disorder (ADHD) have suggested that there is dysregulation of dopamine-mediated neurotransmission, particularly in the prefrontal cortex and basal ganglia, and that treatment with methylphenidate reverses this dysregulation. Using methodology similar to previous studies involving putative markers of brain functioning, we used 1H magnetic resonance spectroscopy to study the effect of 12-week treatment with daily 20-mg long-acting methylphenidate on the glutamate/creatine, N-acetyl-aspartate/creatine, choline/creatine, and myoinositol/creatine ratios in the prefrontal cortices of medication-naive children with ADHD.


METHOD
This was a prospective study, using a pretest and posttest design, on a single group of 21 children (mean age, 8.52 years; 17 males and 4 females) with a diagnosis of ADHD. A low time echo (TE) magnetic resonance spectroscopic scans sampled voxels of interest (1.5 × 1.5 × 2.0) from both the right and left prefrontal cortices.


RESULTS
After treatment, the N-acetyl-aspartate/creatine ratio increased 18.8% in the right prefrontal cortex (P = 0.001) and 10% in the left prefrontal cortex (P = 0.007); the glutamate/creatine ratio decreased 15% in the right prefrontal cortex (P = 0.005) and 14.1% in the left prefrontal cortex (P = 0.005); the choline/creatine ratio decreased 12.4% in the right prefrontal cortex (P = 0.037) and 16% in the left prefrontal cortex (P = 0.006); and the myoinositol/creatine ratio decreased 14.7% in the left prefrontal cortex (P = 0.011) and 7.7% in the right prefrontal cortex (P = 0.129).


CONCLUSION
Notwithstanding the limitations of this pilot study, we found, after stimulant treatment, significant neurochemical changes (thought to reflect functional improvement and improved neuroplasticity) in the prefrontal cortices of children with ADHD.
A layered approach to cognitive radio network security: A survey

Cognitive radios have been identified as a solution to the crowded spectrum issue. With the realization of cognitive radio networks came the recognition that both new and old security threats are relevant. The cognitive radio network is still vulnerable to many of the denial of service, wormhole, routing, and jamming attacks that plague other wireless technologies. In addition, the cognitive radio network is vulnerable to new attacks based on cognitive radio innovations, such as spectrum sharing, spectrum sensing, cognitive capability , and radio reconfigurability. The scope of this survey is to present an overview of security threats and challenges to the cognitive radio network, especially focusing on new solutions from 2012 and the first half of 2013. Included are prior mitigation techniques that are adaptive to the new technology, as well as new mitigation techniques specifically targeted at new cognitive radio vulnerabilities. The threats provided are organized according to the protocol layer at which the attack is targeted. It has been estimated that the people of the United States are now outnumbered by their wireless devices. The proliferation of wireless devices such as laptops, notebooks , cellular phones, smart phones, and tablets has caused the frequency spectrum used for transfer of information to become crowded [70]. Also, the expected growth in media-rich consumer applications and wireless data transfer will continue to further crowd the network, making additional spectrum throughput a priority. Currently in the United States spectrum is allotted to various services in three main categories: licensed, lightly licensed, and unlicensed [1]. Licensed spectrum refers to the portions of the spectrum reserved by each country's equivalent of the Federal Communications Commission (FCC) for specific uses, such as military, public safety, and commercial uses. Lightly licensed spectrum refers to the bands that are generally regulated for licensed users, with regional or other exceptions. In the unlicensed band there are predefined technical rules for the hardware and radio technology intended to mitigate interference between the bands. The spectrum is available for network setup by any person or entity, public or private, to include commercial high speed internet, provided that it does not infringe upon the band's rules [1]. In an effort to provide relief to the users of the overused spectrum, in 2010 the FCC allocated unused spectrum between television channels, or ''white spaces'' for unlicensed use. In addition, the FCC has proposed setting aside some low band spectrum, and possibly underutilized …
Learning, Memory, and the Role of Neural Network Architecture

The performance of information processing systems, from artificial neural networks to natural neuronal ensembles, depends heavily on the underlying system architecture. In this study, we compare the performance of parallel and layered network architectures during sequential tasks that require both acquisition and retention of information, thereby identifying tradeoffs between learning and memory processes. During the task of supervised, sequential function approximation, networks produce and adapt representations of external information. Performance is evaluated by statistically analyzing the error in these representations while varying the initial network state, the structure of the external information, and the time given to learn the information. We link performance to complexity in network architecture by characterizing local error landscape curvature. We find that variations in error landscape structure give rise to tradeoffs in performance; these include the ability of the network to maximize accuracy versus minimize inaccuracy and produce specific versus generalizable representations of information. Parallel networks generate smooth error landscapes with deep, narrow minima, enabling them to find highly specific representations given sufficient time. While accurate, however, these representations are difficult to generalize. In contrast, layered networks generate rough error landscapes with a variety of local minima, allowing them to quickly find coarse representations. Although less accurate, these representations are easily adaptable. The presence of measurable performance tradeoffs in both layered and parallel networks has implications for understanding the behavior of a wide variety of natural and artificial learning systems.