Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Exact Distance Queries on Massive Networks

We present a versatile and scalable algorithm for computing exact distances on real-world networks with tens of millions of arcs in real time. Unlike existing approaches, preprocessing and queries are practical on a wide variety of inputs, such as social, communication, sensor, and road networks. We achieve this by providing a unified approach based on the concept of 2-hop labels, improving upon existing methods. In particular, we introduce a fast sampling-based algorithm to order vertices by importance, as well as effective compression techniques.
Internet Documents: A Rich Source for Spoken Language Modeling

Spoken language speech recognition systems need better understanding of natural spoken language phenomenon than their dictation counterparts. Current language models are mostly based on written text and/or very tedious Wizard of Oz or real dialog experiments1. In this paper we propose to use Internet documents as a very rich source of information for spoken language modeling. Through detailed experiments we show how using Internet we could automatically prepare language models adapted to a given task. For a given recognition system using this approach the word accuracy is up to 15% better than a system using language models trained on written text.
Convergence of multiple pelvic organ inputs in the rat rostral medulla

Electrophysiological recordings were used to investigate the degree of pelvic/visceral convergent inputs onto single medullary reticular formation (MRF) neurons. A total of 94 MRF neurons responsive to bilateral electrical stimulation of the pelvic nerve (PN) in 12 urethane‐anaesthetized male rats were tested for responses to mechanical stimulation of the urinary bladder, urethra, colon and penis, and electrical stimulation of the dorsal nerve of the penis (DNP) and abdominal branches of the vagus. Responses to distension of the bladder were found for 51% (n= 48) of the MRF neurons tested. Of these 48, 71% responded to urethral infusion, 81% responded to colon distension, 100% responded to penile stimulation (and DNP), and 85% responded to vagal stimulation, with 62% responding to stimulation of all four of these territories. This high degree of visceral convergence (i.e. 62%) in a subset of PN‐responsive MRF neurons is significantly greater than for the subset of PN‐responsive MRF neurons that did not respond to urinary bladder distension (i.e. out of the 46 remaining neurons, none responded to all four of the other pelvic/visceral stimuli combined). These results suggest that the neurons processing information from the urinary bladder at this level of the neural axis are likely to be important for mediating interactions between different visceral organs for the coordination of multiple pelvic/visceral functions.
Google now is for the extraverted, cortana for the introverted: investigating the influence of personality on IPA preference

Intelligent Personal Assistants (IPAs) have become a mainstream product and often show a high level of variance in terms of their interaction philosophy. For example, Google's Now has no personality at all, whereas personality plays a strong part in the advertisement of Apple's Siri. We have assessed the personality profile of users and their preference for either Apple's Siri, Google's Now or Microsoft's Cortana, based on attractiveness and psychological state reactance. Analysis revealed how the preference for an IPA depends on a person's character traits. Preferences of individual traits are discussed and average profiles for devotees of different IPAs are given. The results can be used to recommend IPAs specifically to a users' personality profile. The work concludes with a number of recommendations for the design of IPAs to address specific personality traits of users.1
1-Kestose consumption during pregnancy and lactation increases the levels of IgA in the milk of lactating mice

To examine the effect of dietary supplementation with 1-kestose on the IgA levels in milk, BALB/c mice were fed diets with or without 5% 1-kestose during pregnancy and lactation. The total and specific IgA levels in the milk were measured at 7 and 14 days after delivery. A two-way ANOVA with repeated measures resulted in a significant effect of 1-kestose-supplementation on total IgA concentrations (p < 0.05) and the level of anti-Bacteroides IgA (p < 0.05). A significant positive correlation was found between the mean count of Bacteroides spp. in maternal feces and the total IgA concentration in maternal milk (r = 0.55, p < 0.05), suggesting a potential link between the gut and mammary gland immune system. In conclusion, this study demonstrated the effects of dietary prebiotics on milk IgA production. Graphical Abstract Consumption of 1-kestose, a major component of fructooligosaccharides, by pregnant and lactating mice increased the total IgA concentration in the mouse milk.
Structure, stability and function of RNA pseudoknots involved in stimulating ribosomal frameshifting1

Abstract Programmed −1 ribosomal frameshifting has become the subject of increasing interest over the last several years, due in part to the ubiquitous nature of this translational recoding mechanism in pathogenic animal and plant viruses. All cis-acting frameshift signals encoded in mRNAs are minimally composed of two functional elements: a heptanucleotide “slippery sequence” conforming to the general form X XXY YYZ, followed by an RNA structural element, usually an H-type RNA pseudoknot, positioned an optimal number of nucleotides (5 to 9) downstream. The slippery sequence itself promotes a low level (≈1 %) of frameshifting; however, downstream pseudoknots stimulate this process significantly, in some cases up to 30 to 50 %. Although the precise molecular mechanism of stimulation of frameshifting remains poorly understood, significant advances have been made in our knowledge of the three-dimensional structures, thermodynamics of folding, and functional determinants of stimulatory RNA pseudoknots derived from the study of several well-characterized frameshift signals. These studies are summarized here and provide new insights into the structural requirements and mechanism of programmed −1 ribosomal frameshifting.
A Fully-Implantable Wireless System for Human Brain-Machine Interfaces Using Brain Surface Electrodes: W-HERBS

The brain-machine interface (BMI) is a new method for man-machine interface, which enables us to control machines and to communicate with others, without input devices but directly using brain signals. Previously, we successfully developed a real time control system for operating a robot arm using brain-machine interfaces based on the brain surface electrodes, with the purpose of restoring motor and communication functions in severely disabled people such as amyotrophic lateral sclerosis patients. A fully-implantable wireless system is indispensable for the clinical application of invasive BMI in order to reduce the risk of infection. This system includes many new technologies such as two 64-channel integrated analog amplifier chips, a Bluetooth wireless data transfer circuit, a wirelessly rechargeable battery, 3 dimensional tissue-fitting high density electrodes, a titanium head casing, and a fluorine polymer body casing. This paper describes key features of the first prototype of the BMI system for clinical application.
Large discrete jumps observed in the transition between Chern states in a ferromagnetic topological insulator

A quantum Hall insulator is observed to execute large jumps between metastable Chern states. A striking prediction in topological insulators is the appearance of the quantized Hall resistance when the surface states are magnetized. The surface Dirac states become gapped everywhere on the surface, but chiral edge states remain on the edges. In an applied current, the edge states produce a quantized Hall resistance that equals the Chern number C = ±1 (in natural units), even in zero magnetic field. This quantum anomalous Hall effect was observed by Chang et al. With reversal of the magnetic field, the system is trapped in a metastable state because of magnetic anisotropy. We investigate how the system escapes the metastable state at low temperatures (10 to 200 mK). When the dissipation (measured by the longitudinal resistance) is ultralow, we find that the system escapes by making a few very rapid transitions, as detected by large jumps in the Hall and longitudinal resistances. Using the field at which the initial jump occurs to estimate the escape rate, we find that raising the temperature strongly suppresses the rate. From a detailed map of the resistance versus gate voltage and temperature, we show that dissipation strongly affects the escape rate. We compare the observations with dissipative quantum tunneling predictions. In the ultralow dissipation regime, two temperature scales (T1 ~ 70 mK and T2 ~ 145 mK) exist, between which jumps can be observed. The jumps display a spatial correlation that extends over a large fraction of the sample.
Role of endothelium-derived CC chemokine ligand 2 in idiopathic pulmonary arterial hypertension.

RATIONALE Inflammatory cytokines may affect pulmonary vascular remodeling in idiopathic pulmonary arterial hypertension (IPAH). CC chemokine ligand 2 (CCL2) is synthesized by vascular cells and can stimulate monocyte/macrophage migration and smooth muscle cell (SMC) proliferation. OBJECTIVES To investigate the role of CCL2 in IPAH. METHODS CCL2 levels in plasma, monocytes, lungs, and medium from pulmonary endothelial cell (P-EC) or pulmonary artery SMC (PA-SMC) cultures were measured by ELISA and Western blot analysis. CCL2 receptor CCR2 mRNA levels in monocytes, P-ECs, and PA-SMCs were measured by real-time polymerase chain reaction. Effect of CCL2 on PA-SMC proliferation and migration was assessed using [3H]thymidine incorporation and a modified Boyden's chamber. The effect of endothelial cell-derived CCL2 on monocyte migration was measured using a modified Boyden's chamber. MEASUREMENTS AND MAIN RESULTS Compared with control subjects, we found the following in patients with IPAH: elevated CCL2 protein levels in plasma and lung tissue, whereas monocyte CCL2 levels were similar between patients and control subjects, and elevated CCL2 release by P-ECs or PA-SMCs. P-ECs released twice as much CCL2 than did PA-SMCs. Monocyte migration was markedly increased in the presence of P-ECs, and the increase was larger with P-ECs from patients with IPAH. CCL2-blocking antibodies reduced P-ECs' chemotactic activity by 60%. Compared with controls, PA-SMCs from patients exhibited stronger migratory and proliferative responses to CCL2, in keeping with the finding that CCR2 was markedly increased in PA-SMCs from patients. CONCLUSIONS These results suggest that CCL2 overproduction may be a feature of the abnormal P-EC phenotype in IPAH, contributing to the inflammatory process and to pulmonary vascular remodeling.
A randomized controlled clinical study of periodontal tissue regeneration using an extracellular matrix-based resorbable membrane in combination with a collagenated bovine bone graft in intrabony defects

Purpose The purpose of this study was to investigate the feasibility of regenerative therapy with a collagenated bone graft and resorbable membrane in intrabony defects, and to evaluate the effects of the novel extracellular matrix (ECM)-based membrane clinically and radiologically. Methods Periodontal tissue regeneration procedure was performed using an ECM-based resorbable membrane in combination with a collagenated bovine bone graft in intrabony defects around the teeth and implants. A novel extracellular matrix membrane (NEM) and a widely-used membrane (WEM) were randomly applied to the test group and the control group, respectively. Cone-beam computed tomography images were obtained on the day of surgery and 6 months after the procedure. Alginate impressions were taken and plaster models were made 1 week and 6 months postoperatively. Results The quantity of bone tissue, the dimensional changes of the surgically treated intrabony defects, and the changes in width and height below the grafted bone substitutes showed no significant difference between the test and control groups at the 6-month examination. Conclusions The use of NEM for periodontal regeneration with a collagenated bovine bone graft showed similar clinical and radiologic results to those obtained using WEM.
Genetic Variant of C-5434T REN Enhancer on Serum Renin Levels and Binding Pattern of Signal Transducers and Activators Transcription 3

The human renin gene has been widely known to be involved in essential hypertension (EH) pathogenesis. Genetic variant C-5434T of REN enhancer contributed to renin gene transcription and serum renin regulation. However, the mechanism associated with the transcription level changes remains unknown, and only a few reports exist that discussed serum renin levels on C-5434T of REN. Thus, this study aims to investigate the relationship between genetic variant C-5434T of REN enhancer and serum renin levels in Indonesian hypertensive patients. SNP of C-5434T was genotyped in 56 hypertensive patients by using RFLP. The data showed that serum renin is slightly higher in hypertensive patients with the TT genotype (39 ± 10.3) than patients with the CC genotype (33 ± 10.6) but the difference was not statistically significant (p = 0.35). Here, we also present a docking approach for predicting interaction between genetic variant -5434C/T and STAT3 (Signal Transducers and Activators Transcription 3), the predicted transcription factor that regulates renin gene enhancer. The results showed that STAT3-DNA allele T more favorably binds to DNA than STAT3-DNA allele C. These data suggest that the presence of genetic variant C-5434T has changed the binding pattern of STAT3 to REN enhancer. This is likely to influence STAT3 activity to stimulate the expression of renin gene in producing renin.
Perceived Emotional Expression in Synthesized Performances of a Short Melody: Capturing the Listener's Judgment Policy

Recent studies of music performance have shown that systematic variations in tempo, sound level, articulation, and timbre may be used by the performer to communicate representations of specific emotions to listeners. However, although performance analyses show that performers use certain cues to communicate emotions, they cannot explain how listeners use these cues to decode the expression. The purpose of this study was thus to examine listeners' cue utilization. This was done in two listening experiments using synthesized performances of a short melody. In the first experiment, an attempt was made to recreate representative cue profiles of five emotional expressions; happiness, sadness, anger, fear, and tenderness. The cues manipulated included tempo, sound level, spectrum, articulation, attack, vibrato, and timing. Listeners made forced choice judgments regarding the intended emotional expression. The results showed that (a) listeners were successful in decoding the intended emotional expression of the synthesized performances, (b) decoding accuracy was as high for synthesized performances as for live performances, and (c) reversal of the sequences reduced decoding accuracy to a larger extent for live performances than for synthesized performances, suggesting that live performances were relatively more dependent on prosodic contours. In the second experiment, five cues – tempo, sound level, spectrum, articulation, and attack – were systematically varied in a factorial design. Listeners were instructed to describe the emotional expression of each cue combination by ratings on adjective scales. An attempt to describe the listener's judgment policy was made using multiple regression. The results showed that (a) listeners used all of the available cues in their judgments, (b) none of the cues had more than a probabilistic (i.e., uncertain) relation to the listeners' judgments, (c) the predictive strength of each cue varied a lot depending on the emotion judged, and (d) the hypotheses based on our earlier studies of emotional expression in music performance (e.g., Gabrielsson & Juslin, 1996; Juslin; 1997d) were supported.
Turbo covert channel: An iterative framework for covert communication over data networks

Inspired by the challenges of designing a robust, and undetectable covert channel, in this paper we introduce a design methodology for timing covert channels that achieve provable polynomial-time undetectability. This means that the covert channel can not be detected by any polynomial-time statistical test that analyzes the samples of the covert traffic and the legitimate traffic. The proposed framework is based on modeling the covert channel as a differential communication channel, and the formulation for modulation/demodulation processes that are derived according to the communication model. The proposed scheme incorporates a trellis structure in modulating the covert message. The trellis structure is also used at the covert receiver to perform iterative demodulation/decoding of the covert message that significantly enhances the channel reliability. In addition, the paper presents an adaptive modulation strategy that improves the channel robustness without compromising the stealthiness of the channel. The combination of the adaptive modulation and the trellis structure gives the covert channel considerable flexibility and low error rate at the covert receiver. In fact, performance analysis of the channel reveals that the proposed covert communication scheme withstands extremely high levels of network noise and adversarial disruption, while it maintains an outstanding undetectability level and covert rate.
Reprofessionalizing Child Welfare Services: An Evaluation of a Title IVE Training Program

Objective Test the effectiveness of a Title IVE training program for preparing practitioners for public child welfare employment. Method The sample consisted of all workers (N = 266) hired between June 1994 and June 1997 at a public child welfare agency. Data were collected through self-administered questionnaires, a follow-up phone interview, and a review of personnel records. Results Title IV–trained workers scored higher on a test of child welfare knowledge, and they expressed more confidence in their ability to perform basic child welfare tasks than did other workers. Eighty-nine percent of IVE workers were still employed at the study close. Overall, 76% of workers were still employed at that time. Contrary to expectations, IVE workers were not more satisfied with their jobs than other workers. Conclusion The retention finding is encouraging because it may mean that the staffing crisis in child welfare may have a solution in programs like IVE. However, IVE-trained workers may not stay unless the unsatisfactory working conditions are corrected.
The use of one-class classifiers for differentiating healthy from epileptic EEG segments

Epilepsy is the fourth most frequent neurological disorder. Epileptic seizures are the result of temporary electrical disturbances in the brain. This disorder can be diagnosed by electroencephalograms (EEG). Accordingly, data mining supported by machine learning (ML) methods can be used to find patterns in EEG and to build classifiers. However, the presence of physiological abnormalities is considered rare in medical data. Also, rhythmic activities in an EEG of a healthy person varies in different situations, such as with closed or opened eyes. Other issue is that normal and interictal epileptic EEG can contain similar patterns. In this work, we developed classifiers in order to differentiate EEG of healthy volunteers, with opened and closed eyes, from epileptic EEG. This approach was applied in an EEG set with 500 segments, in which cross-correlation and power spectrum methods were performed for feature extraction. Subsequently, predictive models based on one-class classification were built using the one-class support vector machine (OSVM) technique in addition to traditional ML methods, such as nearest-neighbor, artificial neural network, and two-class support vector machine (TSVM). The polynomial and radial basis function (RBF) kernels were applied in OSVM and TSVM. To enable the use of traditional ML methods, the OCC was converted to two-class classification problem through assignment of negative (abnormal) class to each EEG segment that does not belong to normal (positive) class. In the evaluation, it was found that the OSVM classifier with RBF kernel reached the best values for all confusion matrix parameters, such as accuracy, positive predictive value, sensitivity, and false positive rate.
Toward Social-Semantic Recommender Systems

In this article, the authors consider the basic problem of recommender systems that is identifying a set of users to whom a given item is to be recommended. In practice recommender systems are run against huge sets of users, and the problem is then to avoid scanning the whole user set in order to produce the recommendation list. To cope with problem, they consider that users are connected through a social network and that taxonomy over the items has been defined. These two kinds of information are respectively called social and semantic information. In their contribution the authors suggest combining social information with semantic information in one algorithm in order to compute recommendation lists by visiting a limited part of the social network. In their experiments, the authors use two real data sets, namely Amazon.com and MovieLens, and they compare their algorithms with the standard item-based collaborative filtering and hybrid recommendation algorithms. The results show satisfying accuracy values and a very significant improvement of performance, by exploring a small part of the graph instead of exploring the whole graph.
Rapid and sustained health utility gain in anti-tumour necrosis factor-treated inflammatory arthritis: observational data during 7 years in southern Sweden

Background: Rheumatoid arthritis (RA), psoriatic arthritis (PsA) and other spondylarthritides impose a great impact on the individual in addition to the costs on society, which may be reduced by effective pharmacological treatment. Industry-independent health economic studies should complement studies sponsored by industry. Objective: To study secular trends in baseline health utilities in patients commencing tumour necrosis factor (TNF) blockade for arthritis in clinical practice over 7 years; to address utility changes during treatment; to investigate the influence of previous treatment courses; to study the feasibility of health utility measures and to compare them across diagnostic entities. Methods: EuroQoL 5 dimensions (EQ-5D) utility data were collected from a structured clinical follow-up programme of anti-TNF-treated patients with RA (N = 2554), PsA (N = 574) or spondylarthritides (N = 586). Time trends were calculated. Completer analysis was used. Results: There were weak or non-significant secular trends for increasing baseline utilities over time for RA, PsA and spondylarthritides. The maximum gain in utilities had already occurred after 2 weeks for all diagnoses and remained stable for patients remaining on therapy. The first and second anti-TNF courses performed similarly. Conclusions: Utilities at inclusion remained largely unchanged for RA, PsA and spondylarthritides over 7 years. Improvement occurred early during treatment and not beyond 6 weeks at the group level. Improvement during the first course was not consistently greater than the second. There were no major differences between RA, PsA and spondylarthritides. EQ-5D proved feasible and applicable across these diagnoses. These “real world” data may be useful for health economic modelling.