Miracle-dz/UniFAR-FTUs huggingface dataset:
Building Sparse Deep Feedforward Networks using Tree Receptive Fields

Sparse connectivity is an important factor behind the success of convolutional neural networks and recurrent neural networks. In this paper, we consider the problem of learning sparse connectivity for feedforward neural networks (FNNs). The key idea is that a unit should be connected to a small number of units at the next level below that are strongly correlated. We use Chow-Liu's algorithm to learn a tree-structured probabilistic model for the units at the current level, use the tree to identify subsets of units that are strongly correlated, and introduce a new unit with receptive field over the subsets. The procedure is repeated on the new units to build multiple layers of hidden units. The resulting model is called a TRF-net. Empirical results show that, when compared to dense FNNs, TRF-net achieves better or comparable classification performance with much fewer parameters and sparser structures. They are also more interpretable.
{Multi-Player Bandits Revisited}

Multi-player Multi-Armed Bandits (MAB) have been extensively studied in the literature, motivated by applications to Cognitive Radio systems. Driven by such applications as well, we motivate the introduction of several levels of feedback for multi-player MAB algorithms. Most existing work assume that sensing information is available to the algorithm. Under this assumption, we improve the state-of-the-art lower bound for the regret of any decentralized algorithms and introduce two algorithms, RandTopM and MCTopM, that are shown to empirically outperform existing algorithms. Moreover, we provide strong theoretical guarantees for these algorithms, including a notion of asymptotic optimality in terms of the number of selections of bad arms. We then introduce a promising heuristic, called Selfish, that can operate without sensing information, which is crucial for emerging applications to Internet of Things networks. We investigate the empirical performance of this algorithm and provide some first theoretical elements for the understanding of its behavior.
A Functional Variant in ERAP1 Predisposes to Multiple Sclerosis

The ERAP1 gene encodes an aminopeptidase involved in antigen processing. A functional polymorphism in the gene (rs30187, Arg528Lys) associates with susceptibility to ankylosying spondylitis (AS), whereas a SNP in the interacting ERAP2 gene increases susceptibility to another inflammatory autoimmune disorder, Crohn's disease (CD). We analysed rs30187 in 572 Italian patients with CD and in 517 subjects suffering from multiple sclerosis (MS); for each cohort, an independent sex- and age-matched control group was genotyped. The frequency of the 528Arg allele was significantly higher in both disease cohorts compared to the respective control population (for CD, OR = 1.20 95%CI: 1.01–1.43, p = 0.036; for RRMS, OR = 1.26; 95%CI: 1.04–1.51, p = 0.01). Meta-analysis with the Wellcome Trust Cases Control Consortium GWAS data confirmed the association with MS (pmeta = 0.005), but not with CD. In AS, the rs30187 variant has a predisposing effect only in an HLA-B27 allelic background. It remains to be evaluated whether interaction between ERAP1 and distinct HLA class I alleles also affects the predisposition to MS, and explains the failure to provide definitive evidence for a role of rs30187 in CD. Results herein support the emerging concept that a subset of master-regulatory genes underlay the pathogenesis of autoimmunity.
Effects of partial immobilization after eccentric exercise on recovery from muscle damage.

CONTEXT Short-term strict immobilization of the arm using a cast enhances recovery of muscle function after eccentric exercise. OBJECTIVE To determine if placing one arm in a sling ("light" immobilization) for 4 days after eccentric exercise of the elbow flexor muscles would reduce muscle soreness and enhance recovery compared with the exercised but not immobilized contralateral arm. DESIGN Subjects performed 10 sets of 6 maximal isokinetic (90 degrees x s(-1)) eccentric actions of the elbow flexors of each arm on a Cybex dynamometer, separated by 2 weeks. SETTING University laboratory. PATIENTS OR OTHER PARTICIPANTS Ten healthy subjects (5 men and 5 women) with no history of upper arm injury or resistance training. INTERVENTION(S) One randomly assigned arm was placed in a sling for 4 days after the 30-minute postexercise measurement to secure the elbow joint at 90 degrees ; the contralateral arm received no treatment. The subject removed the sling when showering and sleeping and during postexercise measurements. MAIN OUTCOME MEASURE(S) We used an activity monitor to record upper arm activity before and after immobilization. We also compared changes in maximal isometric and isokinetic voluntary strength, range of motion, upper arm circumference, plasma creatine kinase activity, and muscle soreness during 7 days postexercise between arms with a 2-way, repeated-measures analysis of variance. RESULTS Eccentric exercise resulted in large losses in both isometric and isokinetic maximal voluntary contraction forces (approximately 40%), reduced range of motion (approximately 20%), increased arm circumference (approximately 10 mm), elevated plasma creatine kinase activity (approximately 2000 IU x L(-1)), and development of delayed-onset muscle soreness. No significant differences were noted between conditions for any measure except upper arm circumference, which increased significantly less for the immobilization than the control arm at 7 days postexercise (P < .05). CONCLUSIONS Light immobilization had no effect on enhancing recovery of muscle function and delayed-onset muscle soreness after eccentric-exercise-induced muscle damage.
A >40dB IRR, 44% fractional-bandwidth ultra-wideband mm-wave quadrature LO generator for 5G networks in 55nm CMOS

The development of next-generation 5G networks is ongoing. The large available bandwidth at mm-waves allows increasing channel capacity well beyond the levels offered by LTE. Wide ranges of spectra, with sub-bands centered at 28GHz, 37GHz, and 39GHz, have been appointed for 5G development to facilitate international roaming and intra-networks connections [1]. In this scenario, generation of ultra-low phase-noise quadrature (IQ) signals with >40dB image rejection ratio (IRR) over >40% fractional bandwidth is key to efficiently deliver extreme data-rates through high-order spectrally efficient modulations. Quadrature voltage-controlled oscillators are disregarded because of their limited tuning range and also due to a severe trade-off between phase noise and phase accuracy. Solutions leveraging single-phase VCOs followed by quadrature generators is seen as a better strategy. Still, the challenging phase noise, required to support higher-order modulations trading-off with tuning range, mandates at least two VCOs covering half bandwidth each. For quadrature generation, distributed couplers, e.g., Lange couplers, are bulky and not amenable to integration. Hybrid couplers based on coupled inductors offer a compact footprint with low loss, but they are disregarded, because a few percent variation in the coupling coefficient, k, leads to unacceptable phase deviations. Polyphase filters (PPFs) and their improvements are widely adopted at RF [2]. In [3], the PPF operation at mm-waves is proven through careful layout techniques. Still, wideband operation can be achieved only by cascading several stages, severely increasing signal loss and power consumption.
Vision-based attention control system for socially interactive robots

A social robot needs to attract the attention of a target human and shift it from his/her current focus to what is sought by the robot. The robot should recognize the current target's attention level to smoothly perform this attention control. In this paper, we propose a vision-based system to detect the level of attention or willingness of the target person towards the robot and to control his/her attention. The system estimates the attention level from rich visual cues of human's face and head. Then, by timing target's attention to determine the appropriate attention level, it generates aware signals and makes eye contact with the target. Finally, the robot shifts the target's attention to an intended direction. The experimental results reveal that the proposed system is effective in controlling the target's attention.
Control of Mitochondrial Membrane Permeabilization by Adenine Nucleotide Translocator Interacting with HIV-1 Viral Protein R and Bcl-2

Viral protein R (Vpr), an apoptogenic accessory protein encoded by HIV-1, induces mitochondrial membrane permeabilization (MMP) via a specific interaction with the permeability transition pore complex, which comprises the voltage-dependent anion channel (VDAC) in the outer membrane (OM) and the adenine nucleotide translocator (ANT) in the inner membrane. Here, we demonstrate that a synthetic Vpr-derived peptide (Vpr52-96) specifically binds to the intermembrane face of the ANT with an affinity in the nanomolar range. Taking advantage of this specific interaction, we determined the role of ANT in the control of MMP. In planar lipid bilayers, Vpr52-96 and purified ANT cooperatively form large conductance channels. This cooperative channel formation relies on a direct protein–protein interaction since it is abolished by the addition of a peptide corresponding to the Vpr binding site of ANT. When added to isolated mitochondria, Vpr52-96 uncouples the respiratory chain and induces a rapid inner MMP to protons and NADH. This inner MMP precedes outer MMP to cytochrome c. Vpr52-96–induced matrix swelling and inner MMP both are prevented by preincubation of purified mitochondria with recombinant Bcl-2 protein. In contrast to König's polyanion (PA10), a specific inhibitor of the VDAC, Bcl-2 fails to prevent Vpr52-96 from crossing the mitochondrial OM. Rather, Bcl-2 reduces the ANT–Vpr interaction, as determined by affinity purification and plasmon resonance studies. Concomitantly, Bcl-2 suppresses channel formation by the ANT–Vpr complex in synthetic membranes. In conclusion, both Vpr and Bcl-2 modulate MMP through a direct interaction with ANT.
Recent Trends in Knowledge Compilation (Dagstuhl Seminar 17381)

Knowledge compilation (KC) is a research topic which aims to investigate the possibility of circumventing the computational intractability of hard tasks, by preprocessing part of the available information, common to a number of instances. Pioneered almost three decades ago, KC is nowadays a very active research field, transversal to several areas within computer science. Among others, KC intersects knowledge representation, constraint satisfaction, algorithms, complexity theory, machine learning, and databases. The results obtained so far take various forms, from theory (compilability settings, definition of target languages for KC, complexity results, succinctness results, etc.) to more practical results (development and evaluation of compilers and other preprocessors, applications to diagnosis, planning, automatic configuration, etc.). Recently, KC has been positioned as providing a systematic method for solving problems beyond NP, and also found applications in machine learning. The goal of this Dagstuhl Seminar was to advance both aspects of KC, and to pave the way for a fruitful cross-fertilization between the topics, from theory to practice. The program included a mixture of long and short presentations, with discussions. Several long talks with a tutorial flavor introduced the participants to the variety of aspects in knowledge compilation and the diversity of techniques used. System presentations as well as an open problem session were also included in the program.
RNA structure inference through chemical mapping after accidental or intentional mutations

Significance The intricate structures of RNA molecules are crucial to their biological functions but have been difficult to accurately characterize. Multidimensional chemical-mapping methods improve accuracy but have so far involved painstaking experiments and reliance on secondary-structure prediction software. A methodology called M2-seq now lifts these limitations. Mechanistic studies clarify the origin of serendipitous M2-seq–like signals that were recently discovered but not correctly explained and also provide mutational strategies that enable robust M2-seq for new RNA transcripts. The method detects dozens of Watson–Crick helices across diverse RNA folds in vitro and within frog egg extract, with a low false-positive rate (<5%). M2-seq opens a route to unbiased discovery of RNA structures in vitro and beyond. Despite the critical roles RNA structures play in regulating gene expression, sequencing-based methods for experimentally determining RNA base pairs have remained inaccurate. Here, we describe a multidimensional chemical-mapping method called “mutate-and-map read out through next-generation sequencing” (M2-seq) that takes advantage of sparsely mutated nucleotides to induce structural perturbations at partner nucleotides and then detects these events through dimethyl sulfate (DMS) probing and mutational profiling. In special cases, fortuitous errors introduced during DNA template preparation and RNA transcription are sufficient to give M2-seq helix signatures; these signals were previously overlooked or mistaken for correlated double-DMS events. When mutations are enhanced through error-prone PCR, in vitro M2-seq experimentally resolves 33 of 68 helices in diverse structured RNAs including ribozyme domains, riboswitch aptamers, and viral RNA domains with a single false positive. These inferences do not require energy minimization algorithms and can be made by either direct visual inspection or by a neural-network–inspired algorithm called M2-net. Measurements on the P4–P6 domain of the Tetrahymena group I ribozyme embedded in Xenopus egg extract demonstrate the ability of M2-seq to detect RNA helices in a complex biological environment.
Investigating Patterns for Self-Induced Emotion Recognition from EEG Signals

Most current approaches to emotion recognition are based on neural signals elicited by affective materials such as images, sounds and videos. However, the application of neural patterns in the recognition of self-induced emotions remains uninvestigated. In this study we inferred the patterns and neural signatures of self-induced emotions from electroencephalogram (EEG) signals. The EEG signals of 30 participants were recorded while they watched 18 Chinese movie clips which were intended to elicit six discrete emotions, including joy, neutrality, sadness, disgust, anger and fear. After watching each movie clip the participants were asked to self-induce emotions by recalling a specific scene from each movie. We analyzed the important features, electrode distribution and average neural patterns of different self-induced emotions. Results demonstrated that features related to high-frequency rhythm of EEG signals from electrodes distributed in the bilateral temporal, prefrontal and occipital lobes have outstanding performance in the discrimination of emotions. Moreover, the six discrete categories of self-induced emotion exhibit specific neural patterns and brain topography distributions. We achieved an average accuracy of 87.36% in the discrimination of positive from negative self-induced emotions and 54.52% in the classification of emotions into six discrete categories. Our research will help promote the development of comprehensive endogenous emotion recognition methods.
Optimisation du maillage de la veille sur radar à balayage électronique à panneau fixe. (Optimization of search patterns for fixed-panel tridimensional scanning radars)

Modern radars are complex systems, capable of multiple functions: scanning, tracking, identification, etc. With the advent of electronic and digital technologies, radars can dynamically and freely sweep their surroundings using fixed-panels, freeing them from the limitations of mechanical rotation. With increasingly intelligent and adaptable systems competing in modern warfare in ever shorter time, careful management of the radar available time-budget is required to achieve desired performances and ensure civilian and military safety. In this context, optimization of radar search pattern time-budget must exploit modern radars full potential. This thesis main accomplishments are the mathematical modelling of radar search pattern optimization, the identification and development of appropriate tools for its solving, and the exploration of the model possibilities. Radar search pattern design can be related to covering problems in combinatorial optimization. Radar covering can be solved using methods based on dynamic programming and integer programming, and can furthermore be extended to account for more complex situations with multiple operational constraints. The tools developed in this thesis provide a powerful and flexible framework for solving radar covers problems. This framework opens interesting research avenues for improving radar performances. It offers various possible applications for aided-design of radar search patterns, simulation of new radar architectures performances, and development of cognitive radar systems capable of adapting in real time to the operational environment.
FORMULATION AND EVALUATION OF FLURBIPROFEN SOLID DISPERSION

Objective: The present investigation is concerned with the formulation and evaluation of Flurbiprofen solid dispersion and microsphere for prolonging the duration of action of the drug. Method: Flurbiprofen dose is prepared as a capsule containing two types of units; the first one is the fast release unit prepared as a solid dispersion that gives the loading dose for instant pain managements and the other is the controlled release unit which is prepared as microspheres to maintain drug-plasma concentration within the therapeutic level for 24 hours. Microspheres were prepared by solvent evaporation method an using ethyl cellulose and different types of eduragit polymers. The effect of the type and the concentration of polymer, temperature, pH of the continuous phase and the stirring speed were studied, also the release profile, the entrapment efficiency and the particle size were also analyzed to select the best microsphere formula. Results: Microsphere Formula R14 was selected as the best selected formula due to its high entrapment efficiency, high drug loading concentration and its good release profile. A hard gelatin capsule containing Flurbiprofen equivalents to 100mg of fast release dose and 100 mg of controlled release unit was prepared, a further investigation about capsule quality control. Conclusion: The overall results suggested that a solid dispersion and microspheres of flurbiprofen capsule with a better biopharmaceutical propertie and prolonged duration with fast onset of action could be obtained.
The friction of sliding wet textured surfaces: the Bruggeman effective medium approach revisited

The mean field fluid dynamics and the friction occurring in the wet sliding contact between inhomogeneous surfaces, characterized by a deterministically repeated pattern of microdefects, are modelled within the Bruggeman effective medium theory. By comparing with the results of an accurate numerical homogenization of the flow equations, and with asymptotic solutions, we discuss the validity of the mean field model and its limitations in relation to the occurrence of clustering and interference effects. Finally, an analytical upgrade to the Bruggeman approach, allowing for inclusion of the clustering effect, is presented and discussed.
Brachial Plexus Anatomy: Normal and Variant

Effective brachial plexus blockade requires a thorough understanding of the anatomy of the plexus, as well as an appreciation of anatomic variations that may occur. This review summarizes relevant anatomy of the plexus, along with variations and anomalies that may affect nerve blocks conducted at these levels. The Medline, Cochrane Library, and PubMed electronic databases were searched in order to compile reports related to the anatomy of the brachial plexus using the following free terms: "brachial plexus", "median nerve", "ulnar nerve", "radial nerve", "axillary nerve", and "musculocutanous nerve". Each of these was then paired with the MESH terms "anatomy", "nerve block", "anomaly", "variation", and "ultrasound". Resulting articles were hand searched for additional relevant literature. A total of 68 searches were conducted, with a total of 377 possible articles for inclusion. Of these, 57 were found to provide substantive information for this review. The normal anatomy of the brachial plexus is briefly reviewed, with an emphasis on those features revealed by use of imaging technologies. Anomalies of the anatomy that might affect the conduct of the various brachial plexus blocks are noted. Brachial plexus blockade has been effectively utilized as a component of anesthesia for upper extremity surgery for a century. Over that period, our understanding of anatomy and its variations has improved significantly. The ability to explore anatomy at the bedside, with real-time ultrasonography, has improved our appreciation of brachial plexus anatomy as well.
Ciphertext policy attribute-based encryption supporting unbounded attribute space from R-LWE

Ciphertext policy attribute-based encryption (CP-ABE) is a useful cryptographic technology for guaranteeing data confidentiality but also fine-grained access control. Typically, CP-ABE can be divided into two classes: small universe with polynomial attribute space and large universe with unbounded attribute space. Since the learning with errors over rings (R-LWE) assumption has characteristics of simple algebraic structure and simple calculations, based on R-LWE, we propose a small universe CP-ABE scheme to improve the efficiency of the scheme proposed by Zhang et al . (AsiaCCS 2012). On this basis, to achieve unbounded attribute space and improve the expression of attribute, we propose a large universe CP-ABE scheme with the help of a full-rank differences function. In this scheme, all polynomials in the R-LWE can be used as values of an attribute, and these values do not need to be enumerated at the setup phase. Different trapdoors are used to generate secret keys in the key generation and the security proof. Both proposed schemes are selectively secure in the standard model under R-LWE. Comparison with other schemes demonstrates that our schemes are simpler and more efficient. R-LWE can obtain greater efficiency, and unbounded attribute space means more flexibility, so our research is suitable in practices
Identification and Characterization of Wheat Yellow Striate Virus, a Novel Leafhopper-Transmitted Nucleorhabdovirus Infecting Wheat

A new wheat viral disease was found in China. Bullet-shaped viral particles within the nucleus of the infected wheat leave cells, which possessed 180–210 nm length and 35–40 nm width, were observed under transmission electron microscopy. A putative wheat-infecting rhabdovirus vectored by the leafhopper Psammotettix alienus was identified and tentatively named wheat yellow striate virus (WYSV). The full-length nucleotide sequence of WYSV was determined using transcriptome sequencing and RACE analysis of both wheat samples and leafhoppers P. alienus. The negative-sense RNA genome of WYSV contains 14,486 nucleotides (nt) and seven open reading frames (ORFs) encode deduced proteins in the order N-P-P3-M-P6-G-L on the antisense strand. In addition, WYSV genome has a 76-nt 3′ leader RNA and a 258-nt 5′ trailer, and the ORFs are separated by conserved intergenic sequences. The entire genome sequence shares 58.1 and 57.7% nucleotide sequence identity with two strains of rice yellow stunt virus (RYSV-A and RYSV-B) genomes, respectively. The highest amino acid sequence identity was 63.8% between the L proteins of the WYSV and RYSV-B, but the lowest was 29.5% between the P6 proteins of these viruses. Phylogenetic analysis firmly established WYSV as a new member of the genus Nucleorhabdovirus. Collectively, this study provided evidence that WYSV is likely the first nucleorhabdovirus described infecting wheat via leafhopper P. alienus transmission.