Miracle-dz/UniFAR-FTUs huggingface dataset:
Set-Based Unified Approach for Attributed Graph Summarization

In this paper we combine the neighborhood and attributes similarity to summarize big graphs where each node is attached with multiple attributes. The main intution behind our approach is that sets of nodes having common links, in graphs, usually have same attributes. Thus compressing such Sets of Similar Nodes (SSNs) can significantly reduce the size of big graphs, yet preserving the overall properties of the underlying graphs. However, efficiently finding such sets is computationally expensive. Finding these using pair wise similarity computations is not scalable while exploiting the nodes ordering in graphs, does not consider their attributes. For this purpose we propose a Unified Locality Sensitive Hashing (ULSH) approach to approximate the SSNs, since in graphs LSH can assemble the nodes based on neighborhood similarity only. Further using Minimum Description Length (MDL) principle, we propose a Unified Graph Summarization (UGS) technique to perform lossless compression of each set by creating a super node or adding a new virtual node in the graph. We compare our approach with two state of the art methods by experiments on synthetic and publically available real world graphs and observe very encouraging results.
The Impact of Explanation Facilities on Decision Support Systems Includes Multiple Knowledge Domains

DSS depends not only on the accuracy of the results, but also on acceptance of these results by its users. Research in the field of DSS has shown that providing explanations may improve the acceptance. Decision making process includes the procedures of decision and the support of different knowledge, to reveal such process will help people understand and audit the results of DSS. This paper attempts to provide an explanation mechanism for decision making process which includes different knowledge domains. First, a process of cognitive is described to show how decisions are made. Second, the trace of knowledge domains is used to establish the pattern of decision making process. Finally, a framework of comparison between decisions is provided.
A holistic evolutionary and structural study of flaviviridae provides insights into the function and inhibition of HCV helicase

Viral RNA helicases are involved in duplex unwinding during the RNA replication of the virus. It is suggested that these helicases represent very promising antiviral targets. Viruses of the flaviviridae family are the causative agents of many common and devastating diseases, including hepatitis, yellow fever and dengue fever. As there is currently no available anti-Flaviviridae therapy, there is urgent need for the development of efficient anti-viral pharmaceutical strategies. Herein, we report the complete phylogenetic analysis across flaviviridae alongside a more in-depth evolutionary study that revealed a series of conserved and invariant amino acids that are predicted to be key to the function of the helicase. Structural molecular modelling analysis revealed the strategic significance of these residues based on their relative positioning on the 3D structures of the helicase enzymes, which may be used as pharmacological targets. We previously reported a novel series of highly potent HCV helicase inhibitors, and we now re-assess their antiviral potential using the 3D structural model of the invariant helicase residues. It was found that the most active compound of the series, compound C4, exhibited an IC50 in the submicromolar range, whereas its stereoisomer (compound C12) was completely inactive. Useful insights were obtained from molecular modelling and conformational search studies via molecular dynamics simulations. C12 tends to bend and lock in an almost “U” shape conformation, failing to establish vital interactions with the active site of HCV. On the contrary, C4 spends most of its conformational time in a straight, more rigid formation that allows it to successfully block the passage of the oligonucleotide in the ssRNA channel of the HCV helicase. This study paves the way and provides the necessary framework for the in-depth analysis required to enable the future design of new and potent anti-viral agents.
Psychosocial Intervention Is Associated with Altered Emotion Processing: An Event-Related Potential Study in At-Risk Adolescents

Emotion processing is vital for healthy adolescent development, and impaired emotional responses are associated with a number of psychiatric disorders. However, it is unclear whether observed differences between psychiatric populations and healthy controls reflect modifiable variations in functioning (and thus could be sensitive to changes resulting from intervention) or stable, non-modifiable, individual differences. The current study therefore investigated whether the Late Positive Potential (LPP; a neural index of emotion processing) can be used as a marker of therapeutic change following psycho-social intervention. At-risk male adolescents who had received less than four months intervention (minimal-intervention, N = 32) or more than nine months intervention (extended-intervention, N = 32) passively viewed emotional images whilst neural activity was recorded using electroencephalography. Significant differences in emotion processing, indicated by the LPP, were found between the two groups: the LPP did not differ according to valence in the minimal-intervention group, whereas the extended-intervention participants showed emotion processing in line with low risk populations (enhanced LPP for unpleasant images versus other images). Further, an inverse relationship between emotional reactivity (measured via the LPP) and antisocial behaviour was observed in minimal-intervention participants only. The data therefore provide preliminary cross-sectional evidence that abnormal neural responses to emotional information may be normalised following psychosocial intervention. Importantly, this study uniquely suggests that, in future randomised control trials, the LPP may be a useful biomarker to measure development and therapeutic change.
PTPN22 R620W Functional Variant in Type 1 Diabetes and Autoimmunity Related Traits

The PTPN22 gene, encoding the lymphoid-specific protein tyrosine phosphatase, a negative regulator in the T-cell activation and development, has been associated with the susceptibility to several autoimmune diseases, including type 1 diabetes. Based on combined case-control and family-based association studies, we replicated the finding of an association of the PTPN22 C1858T (R620W) functional variant with type 1 diabetes, which was independent from the susceptibility status at the insulin gene and at HLA-DR (DR3/4 compared with others). The risk contributed by the 1858T allele was increased in patients with a family history of other autoimmune diseases, further supporting a general role for this variant on autoimmunity. In addition, we found evidence for an association of 1858T allele with the presence of GAD autoantibodies (GADA), which was restricted to patients with long disease duration (>10 years, P < 0.001). This may help define a subgroup of patients with long-term persistence of GADA. The risk conferred by 1858T allele on GAD positivity was additive, and our meta-analysis also supported an additive rather than dominant effect of this variant on type 1 diabetes, similar to previous reports on rheumatoid arthritis and systemic lupus erythematosus.
Probability of error and ergodic capacity of switch-and-examine combining diversity over the α-μ fading channel

In this paper, we consider a switch-and-examine combining (SEC) diversity scheme operating over independent and identically distributed (i.i.d) branches assuming an α-μ fading channel. We derive expressions for the average symbol error rate (ASER) for a class of coherent modulation techniques considering this fading model as well as expressions for the ergodic capacity under the same assumptions. The results for the ASER and the ergodic capacity are shown to reduce to those previously reported in the literature for other channel models such as the Weibull model as a special case, which confirms the validity of the obtained expressions. Different aspects are studied including the effect of fading severity, the number of branches and the modulation scheme used. Also, insights on the optimal choice of the switching threshold are provided.
Optimization of the Ocular Treatment Following Organophosphate Nerve Agent Insult

Eye exposure to organophosphate (OP) irreversible acetylcholinesterase inhibitors, results in long-term miosis and impaired visual function. The aim of this study was to find an anticholinergic antidote, which would counteract miosis and visual impairment induced by the nerve agents sarin and VX with minimal untoward side-effects. Rat pupil width and light reflex were evaluated from 15 min up to 2 weeks following topical OP exposure with or without topical ocular treatment of atropine or homatropine or with a combined intramuscular treatment of trimedoxime (TMB-4) and atropine (TA). Visual function following insult and treatment was assessed using a cued Morris water maze task. Topical VX exposure showed a dose-dependent miosis with a significant reduction in visual function similar to the effect seen following sarin exposure. Homatropine (2%; w/v) and atropine (0.1%; w/v) treatment ameliorated both sarin and VX-induced miosis and the resulting visual impairment. TA treatment was sufficient in ameliorating the sarin-induced ocular impairment while an additional ocular treatment with either 0.1% atropine or 2% homatropine was necessary following VX exposure. To conclude the use of 0.1% atropine or 2% homatropine was beneficial in ameliorating the ocular insult following VX or sarin ocular exposure and thus should be considered as universal treatments against this intoxication. The findings also emphasize the necessity of additional ocular treatment to the systemic treatment in visually impaired casualties following VX exposure.
Application of modified wavelet features and multi-class sphere SVM to pathological vocal detection

This paper researches the method of wavelet feature-vectors and multi-class support vector machines applied to pathological vocal detection, which extracts features of the pathological vocal based on continuous wavelet transformation and then classifies pathological vocal by multi - class support vector machine. In order to reduce computation complexity caused by using the standard support vector machines for multi-class classification, a new multi-class classification algorithm based on the idea of one-class classification is proposed. It can form a decision function for every single class sample and accordingly obtain the aim of classification based on maximum of decision function. Experimental results have shown that the pathological vocal detection system is feasible and applicable by the combination of multi-class SVM and wavelet feature-vectors.
Computer user verification using login string keystroke dynamics

The keystroke dynamics of a computer user's login string provide a characteristic pattern that can be used for identity verification. Timing vectors for several hundred login attempts were collected for ten "valid" users and ten "forgers", and classification analysis was applied to discriminate between them. Three different classifiers were applied, and in each case the key hold times were more effective features for discrimination than the interkey times. Best performance was achieved by an inductive learning classifier using both interkey and hold times. A high rate of typographical errors during login entry is reported. In practice, these are usually corrected errors-that is, they are strings which include backspaces to correct earlier errors-but their presence confounds the use of typing-style analysis as a practical means of securing access to computer systems.
Undaria pinnatifida: A case study to highlight challenges in marine invasion ecology and management

Abstract Marine invasion ecology and management have progressed significantly over the last 30 years although many knowledge gaps and challenges remain. The kelp Undaria pinnatifida, or “Wakame,” has a global non‐native range and is considered one of the world's “worst” invasive species. Since its first recorded introduction in 1971, numerous studies have been conducted on its ecology, invasive characteristics, and impacts, yet a general consensus on the best approach to its management has not yet been reached. Here, we synthesize current understanding of this highly invasive species and adopt Undaria as a case study to highlight challenges in wider marine invasion ecology and management. Invasive species such as Undaria are likely to continue to spread and become conspicuous, prominent components of coastal marine communities. While in many cases, marine invasive species have detectable deleterious impacts on recipient communities, in many others their influence is often limited and location specific. Although not yet conclusive, Undaria may cause some ecological impact, but it does not appear to drive ecosystem change in most invaded regions. Targeted management actions have also had minimal success. Further research is needed before well‐considered, evidence‐based management decisions can be made. However, if Undaria was to become officially unmanaged in parts of its non‐native range, the presence of a highly productive, habitat former with commercial value and a broad ecological niche, could have significant economic and even environmental benefit. How science and policy reacts to the continued invasion of Undaria may influence how similar marine invasive species are handled in the future.
INEQUALITIES FOR RARE EVENTS IN TIME-REVERSIBLE MARKOV CHAINS I

The distribution of waiting time until a rare event is often approximated by the exponential distribution. In the context of first hitting times for stationary reversible chains, the error has a simple explicit bound involving only the mean waiting time ET and the relaxation time r of the chain. We recall general upper and lower bounds on ET and then discuss improvements available in the case ET >> τ where the exponential approximation holds. In a sequel, Stein's method will be used to get explicit bounds on the Poisson approximation for the number of non-adjacent visits to a rare subset.
Tandem LSTM-SVM Approach for Sentiment Analysis

English. In this paper we describe our approach to EVALITA 2016 SENTIPOLC task. We participated in all the subtasks with constrained setting: Subjectivity Classification, Polarity Classification and Irony Detection. We developed a tandem architecture where Long Short Term Memory recurrent neural network is used to learn the feature space and to capture temporal dependencies, while the Support Vector Machines is used for classification. SVMs combine the document embedding produced by the LSTM with a wide set of general–purpose features qualifying the lexical and grammatical structure of the text. We achieved the second best accuracy in Subjectivity Classification, the third position in Polarity Classification, the sixth position in Irony Detection. Italiano. In questo articolo descriviamo il sistema che abbiamo utilizzato per affrontare i diversi compiti del task SENTIPOLC della conferenza EVALITA 2016. In questa edizione abbiamo partecipato a tutti i sotto compiti nella configurazione vincolata, cioè senza utilizzare risorse annotate a mano diverse rispetto a quelle distribuite dagli organizzatori. Per questa partecipazione abbiamo sviluppato un metodo che combina una rete neurale ricorrente di tipo Long Short Term Memory, utilizzate per apprendere lo spazio delle feature e per catturare dipendenze temporali, e Support Vector Machine per la classificazione. Le SVM combinano la rappresentazione del documento prodotta da LSTM con un ampio insieme di features che descrivono la struttura lessicale e grammaticale del testo. Attraverso questo sistema abbiamo ottenuto la seconda posizione nella classificazione della Soggettività, la terza posizione nella classificazione della Polarità e la sesta nella identificazione dell’Ironia. 1 Description of the system We addressed the EVALITA 2016 SENTIPOLC task (Barbieri et al., 2016) as a three-classification problem: two binary classification tasks (Subjectivity Classification and Irony Detection) and a four-class classification task (Polarity Classification). We implemented a tandem LSTM-SVM classifier operating on morpho-syntactically tagged texts. We used this architecture since similar systems were successfully employed to tackle different classification problems such keyword spotting (Wöllmer et al., 2009) or the automatic estimation of human affect from speech signal (Wöllmer et al., 2010), showing that tandem architectures outperform the performances of the single classifiers. In this work we used Keras (Chollet, 2016) deep learning framework and LIBSVM (Chang et al., 2001) to generate respectively the LSTM and the SVMs statistical models. Since our approach relies on morphosyntactically tagged texts, both training and test data were automatically morphosyntactically tagged by the POS tagger described in (Dell’Orletta, 2009). In addition, in order to improve the overall accuracy of our system (described in 1.2), we developed sentiment polarity and word embedding lexicons described below. All the created lexicons are made freely available at the following website: http://www.italianlp. it/.
Spatial Resolution Improvement in Correlation Domain Distributed Measurement of Brillouin Grating

We have demonstrated that intensity modulation enhances the spatial resolution in the distributed measurement of Brillouin dynamic grating (BDG) spectrum by the Brillouin optical correlation domain analysis. According to the correlation domain principle, the stimulated Brillouin scattering is localized in so-called correlation peaks, but these peaks actually have side lobes, which excite the BDG out of the peak region, compromising the spatial resolution in the BDG spectrum measurement. To solve this, we applied intensity modulation to apodize the optical power spectrum of the input lightwave to the system, suppressing the side lobes. We experimentally confirmed about 4.5 times improvement in the spatial resolution. A 25-cm-long stressed segment in a 500-m-long fiber was successfully recognized in the proposed system, which could not be achieved by a system without the intensity modulation.
Reliability, validity and clinical usefulness of the BNI fatigue scale in mild traumatic brain injury

Objectives: The purpose of this study was to examine the reliability, validity and clinical usefulness of the Barrow Neurological Institute Fatigue Scale (BNI-FS) in patients with mild traumatic brain injuries (MTBI). Methods and procedure: Participants were 125 patients enrolled from the Emergency Department (ED) of Tampere University Hospital, Finland who had sustained an MTBI. The average number of days from injury to the interview and questionnaires was 24.1 (SD = 5.4, Range = 8–38). The patients were compared to a healthy control sample. Patients completed the Barrow Neurological Institute Fatigue Scale, Fatigue Impact Scale (FIS), Beck Depression Inventory-Second Edition (BDI-II), Rivermead Post-concussion Symptom Questionnaire (RPSQ) and the health assessment measure EuroQol five Dimension (EQ-5D) Visual Analogue Scale (VAS). Results: The MTBI group had significantly greater total scores on the BNI-FS than the control group (p < 0.005, Cohen's d = 0.40). The internal consistency reliability for the BNI-FS, as measured by Cronbach's alpha, was 0.96 for the MTBI group and 0.87 for the control group. The 10 items were submitted to an exploratory principal components factor analysis with varimax rotation in the MTBI group. A one-factor solution, accounting for 73.3% of the total variance, appropriately summarized the data. The correlation between the BNI-FS and other measures was rs = 0.68 (p < 0.001) for the BDI-II, rs = 0.68 (p < 0.001) for the RPSQ, rs = −0.39 (p < 0.001) for the EQ-5D VAS and rs = 0.84 (p < 0.001) for the FIS. Fatigue ratings correlated positively with number of days post-injury before returning to work (rs = 0.27, p < 0.006). Conclusion: The BNI-FS is a relatively new, brief and highly reliable measure of fatigue.
A NEW SPECIES OF SPHAEROMYXA (MYXOSPOREA: SPHAEROMYXINA: SPHAEROMYXIDAE) IN DEVIL FIREFISH, PTEROIS MILES (SCORPAENIDAE), FROM THE NORTHERN RED SEA: MORPHOLOGY, ULTRASTRUCTURE, AND PHYLOGENY

Sphaeromyxa zaharoni n. sp. (Myxosporea) is described from the gallbladder of devil firefish, Pterois miles (Scorpaenidae), from coral reefs of the Gulf of Eilat, Israel, northern Red Sea. The parasite was found also in bearded scorpionfish, Scorpaenopsis barbata, from the same area. This is the first report on Sphaeromyxa sp. from this zoogeographical region. The plasmodia are amoeboid when young, becoming disc-shaped and elongated when mature. In paraffin sections, the plasmodium periphery appears as a finely granulated, strongly eosinophilic layer with an intricate surface membrane network. Sphaeromyxa zaharoni n. sp. is polysporous, disporoblastic, and has asynchronous sporogenesis. The mature spore is elongated and fusiform, has delicately ridged valves, and contains a single, binucleated sporoplasm. In valvular view, the tips are truncated. The mean spore size is length 14.5 μm, width 4.8 μm, and polar capsule 4.8 × 3.4 μm. The 2 equally sized ovoid polar capsules are positioned at opposite ends of the spore, each containing a filament loosely folded in 2 loops. The fine structure of the sporoblast and spore corresponded with previously studied Sphaeromyxa species. According to small-subunit ribosomal DNA gene sequence analysis, S. zaharoni n. sp. is most closely related to 2 Myxidium spp. The close phylogenetic relatedness of Sphaeromyxa and Myxidium and similar spore morphology raises the question whether these 2 genera should be maintained in separate families and suborders.
A v-band power amplifier with adaptive bias circuit to save quiescent DC power consumption using 90-nm CMOS technology

A 60 GHz three-stage power amplifier with auto bias control is realized in 90-nm CMOS low-power process. A feed-forward type adaptive bias circuit using an envelope detector is proposed to reduce the dc power consumption in low power operation. This PA provides 13.8-dB linear gain with a quiescent dc power of 100 mW. In high power operating region, it delivers OPidB 11 dBm and 12.7-dBm saturation output power with 168 mW dc power consumption. Compared with fixed bias operation, this technique saves about 40% dc power consumption in low power operating region.
Conjugate Codes for Secure and Reliable Information Transmission

A conjugate code pair is defined as a pair of linear codes either of which contains the dual of the other. A conjugate code pair represents the essential structure of the corresponding Calderbank-Shor-Steane (CSS) quantum code. It is known that conjugate code pairs are applicable to (quantum) cryptography. In this work, polynomially constructible and efficiently decodable conjugate code pairs are presented. The constructed pairs achieve the highest known achievable rate on additive channels.