Miracle-dz/UniFAR-FTUs huggingface dataset:
FONN: Combining First Order Logic with Connectionist Learning

This paper presents a neural network architecture that can manage structured data and reene knowledge bases expressed in a rst order logic language. The presented framework is well suited to classiication problems in which concept descriptions depend upon numerical features of the data. In fact, the main goal of the neural architecture is that of reening the numerical part of the knowledge base, without changing its structure. In particular, we discuss a method to translate a set of classiication rules into neural computation units. Here, we focus our attention on the translation method and on algorithms to reene network weights on struc-tured data. The classiication theory to be reened can be manually handcrafted or automatically acquired by a symbolic relational learning system able to deal with numerical features. As a matter of fact, the primary goal is to bring into a neural network architecture the capability of dealing with structured data of unrestricted size, by allowing to dynamically bind the classiication rules to diierent items occurring in the input data. An extensive experimentation on a challenging artiicial case study shows that the network converges quite fastly and generalizes much better than propositional learners on an equivalent task deenition.
Nicotinic Enhancement of the Noradrenergic Inhibition of Sleep-Promoting Neurons in the Ventrolateral Preoptic Area

According to multiple lines of evidence, neurons in the ventrolateral preoptic area (VLPO) that contain GABA promote sleep by inhibiting neurons of the arousal systems. Reciprocally, transmitters used by these systems, including acetylcholine (ACh) and noradrenaline (NA), exert an inhibitory action on the VLPO neurons. Because nicotine, an agonist of ACh, acts as a potent stimulant, we queried whether it might participate in the cholinergic inhibition of these sleep-promoting cells. Indeed, we found that ACh inhibits the VLPO neurons through a nicotinic, as well as a muscarinic, action. As evident in the presence of atropine, the non-muscarinic component was mimicked by epibatidine, a nonselective nicotinic ACh receptor (nAChR) agonist and was blocked by dihydro-β-erythroidine, a nonselective nAChR antagonist. It was not, however, blocked by methyllycaconitine, a selective antagonist of the α7 subtype, indicating that the action was mediated by non-α7 nAChRs. The nicotinic inhibition was attributed to a presynaptic facilitation of NA release because it persisted in the presence of tetrodotoxin and was blocked by yohimbine and RS 79948, which are both selective antagonists of α2 adrenergic receptors. Sleep-promoting VLPO neurons are thus dually inhibited by ACh through a muscarinic postsynaptic action and a nicotinic presynaptic action on noradrenergic terminals. Such dual complementary actions allow ACh and nicotine to enhance wakefulness by inhibiting sleep-promoting systems while facilitating other wake-promoting systems.
Mannose binding lectin and mannose binding lectin‐associated serine protease‐2 genes polymorphisms in human T‐lymphotropic virus infection

Variations in genes involved in the immune response pathways may influence the interaction between viruses (such as Human T‐lymphotropic virus, HTLV‐1) and the host. The mannose binding lectin (MBL) and its associated serine protease type 2 (MASP‐2) promote the activation of the lectin pathway of the complement system. As the interaction of complement system with HTLV‐1 is not well understood, the MBL2 promoter/exon 1 polymorphisms and a MASP2 missense polymorphism were examined in a Northeast Brazilian population, looking for a possible relationship between these variations and the susceptibility to HTLV‐1 infection. The present study describes an association between a polymorphism in the MASP2 gene and susceptibility to HTLV‐1 infection, and provides further evidence of an association between the MBL2 gene and HTLV‐1 infection. These findings suggest an important role of the complement system activation, via the lectin pathway, in the susceptibility to HTLV‐1 infection. J Med. Virol. 85:1829–1835, 2013. © 2013 Wiley Periodicals, Inc.
Fat Caches for Scale-Out Servers

Emerging scale-out servers are characterized by massive memory footprints and bandwidth requirements. On-chip stacked DRAM caches have been proposed to provide the required bandwidth for manycore servers through caching of secondary data working sets. However, the disparity between provided capacity and working set sizes precludes their effective deployment in servers, calling for high-capacity cache architectures. High-capacity caches--enabled by the emergence of high-bandwidth memory technologies--exhibit high spatiotemporal locality due to coarse-grained access patterns and long cache residency periods stemming from skewed dataset access distributions. The observed spatiotemporal behavior favors a page-based organization that naturally exploits spatial locality while minimizing tag storage requirements and enabling a practical in-SRAM tag array architecture. By storing tags in SRAM, caches avoid the complexity of in-DRAM metadata found in state-of-the-art DRAM caches.
Sensoric Protection after Median Nerve Injury: Babysitter-Procedure Prevents Muscular Atrophy and Improves Neuronal Recovery

The babysitter-procedure might offer an alternative when nerve reconstruction is delayed in order to overcome muscular atrophy due to denervation. In this study we aimed to show that a sensomotoric babysitter-procedure after median nerve injury is capable of preserving irreversible muscular atrophy. The median nerve of 20 female Wistar rats was denervated. 10 animals received a sensory protection with the N. cutaneous brachii. After six weeks the median nerve was reconstructed by autologous nerve grafting from the contralateral median nerve in the babysitter and the control groups. Grasping tests measured functional recovery over 15 weeks. At the end of the observation period the weight of the flexor digitorum sublimis muscle was determined. The median nerve was excised for histological examinations. Muscle weight (P < 0.0001) was significantly superior in the babysitter group compared to the control group at the end of the study. The histological evaluation revealed a significantly higher diameter of axons (P = 0.0194), nerve fiber (P = 0.0409), and nerve surface (P = 0.0184) in the babysitter group. We conclude that sensory protection of a motor nerve is capable of preserving muscule weight and we may presume that metabolism of the sensory nerve was sufficient to keep the target muscle's weight and vitality.
Title Novel Epitopic Region of Glucosyltransferase B from Streptococcusmutans

In the development of a component vaccine against caries, the catalytic region (CAT) and glucan-binding domain (GBD) of glucosyltransferase B (GtfB) from Streptococcus mutans have been employed as target antigens. These regions were adopted as primary targets because they theoretically include epitopes associated with enzyme function. However, their antigenicity has not been fully evaluated. Although there are many reports about successful vaccination using these components, the principle has not yet been put to practical use. For these reasons, we came to doubt the effectiveness of the epitopes in vaccine production and reevaluated the antigenic region of GtfB using in silico analyses combined with in vitro and in vivo experiments. The results suggest that the ca. 360-amino-acid variable region (VR) in the N-terminus of GtfB would be more reactive than CAT and GBD. This region is S. mutansand/or GtfB-specific, non-conserved among other streptococcal Gtfs, and of unknown function. Immunization using an adenovirus vector-borne DNA vaccine confirmed that VR is an epitope that shows promise for the development of a caries vaccine.
Evolutionary Strata on the Chicken Z Chromosome: Implications for Sex Chromosome Evolution

The human X chromosome exhibits four “evolutionary strata,” interpreted to represent distinct steps in the process whereby recombination became arrested between the proto X and proto Y. To test if this is a general feature of sex chromosome evolution, we studied the Z-W sex chromosomes of birds, which have female rather than male heterogamety and evolved from a different autosome pair than the mammalian X and Y. Here we analyze all five known gametologous Z-W gene pairs to investigate the “strata” hypothesis in birds. Comparisons of the rates of synonymous substitution and intronic divergence between Z and W gametologs reveal the presence of at least two evolutionary strata spread over the p and q arms of the chicken Z chromosome. A phylogenetic analysis of intronic sequence data from different avian lineages indicates that Z-W recombination ceased in the oldest stratum (on Zq; CHD1Z, HINTZ, and SPINZ) 102–170 million years ago (MYA), before the split of the Neoaves and Eoaves. However, recombination continued in the second stratum (on Zp; UBAP2Z and ATP5A1Z) until after the divergence of extant avian orders, with Z and W diverging 58–85 MYA. Our data suggest that progressive and stepwise cessation of recombination is a general feature behind sex chromosome evolution.
The perils of taxonomic inconsistency in quantitative palaeoecology: experiments with testate amoeba data

Payne, R. J., Lamentowicz, M. & Mitchell, E. A. D. 2010: The perils of taxonomic inconsistency in quantitative palaeoecology: experiments with testate amoeba data. Boreas, 10.1111/j.1502‐3885.2010. 00174.x. ISSN 0300‐9483.
The Impact of Tax and Expenditure Policies on Income Distribution: Evidence from a Large Panel of Countries

This paper focuses is on the potential role that taxation and public expenditure policies play in general in affecting income distribution. We find that progressive personal income taxes and corporate income taxes reduce income inequality. However, the effect of corporate income taxes seems to be eroded away in open or globalized economies. We also find that general consumption taxes, excise taxes and customs duties have a negative impact on income distribution. on the expenditure side, we find that higher shares of GDP on social welfare, education, health and housing public expenditures have a positive impact on income distribution.
Cell repolarization variability modulates atrial fibrillation dynamics in 3D virtual human atria

Intersubject variability in cardiac electrophysiology might determine the patient-specific proneness to suffer and/or sustain arrhythmia episodes, such as atrial fibrillation (AF). However, its potential influence on arrhythmogenesis is not well understood. In this study, we compare AF activity in virtual 3D human atria models with notable differences in cellular repolarization dynamics, in order to investigate mechanisms of intersubject variability. Physiological populations of models representing myocytes of patients with chronic AF were obtained and divided into sub-populations depending on the action potential duration (APD) measured at 90%, 50% and 20% repolarization. Each sub-population was used to build a model of the human atria. Analysis of calculated pseudo-electrograms showed the dominant frequency was in general higher for the short APD than for the long APD sub-populations. Organisation indices presented similar values for both APD90 sub-populations, whereas they were higher for the short APD50 and APD20 sub-populations, respectively. Regularity indices were lower for the short APD sub-populations. In conclusion, our results indicate that patients with long atrial APD could be associated with slow but very regular fibrillatory patterns, whereas short APDs may entail high frequency reentrant rotors and larger organisation.
Normalized Affymetrix expression data are biased by G-quadruplex formation

Probes with runs of four or more guanines (G-stacks) in their sequences can exhibit a level of hybridization that is unrelated to the expression levels of the mRNA that they are intended to measure. This is most likely caused by the formation of G-quadruplexes, where inter-probe guanines form Hoogsteen hydrogen bonds, which probes with G-stacks are capable of forming. We demonstrate that for a specific microarray data set using the Human HG_U133A Affymetrix GeneChip and RMA normalization there is significant bias in the expression levels, the fold change and the correlations between expression levels. These effects grow more pronounced as the number of G-stack probes in a probe set increases. Approximately 14% of the probe sets are directly affected. The analysis was repeated for a number of other normalization pipelines and two, FARMS and PLIER, minimized the bias to some extent. We estimate that ∼15% of the data sets deposited in the GEO database are susceptible to the effect. The inclusion of G-stack probes in the affected data sets can bias key parameters used in the selection and clustering of genes. The elimination of these probes from any analysis in such affected data sets outweighs the increase of noise in the signal.
Understanding class-level testability through dynamic analysis

It is generally acknowledged that software testing is both challenging and time-consuming. Understanding the factors that may positively or negatively affect testing effort will point to possibilities for reducing this effort. Consequently there is a significant body of research that has investigated relationships between static code properties and testability. The work reported in this paper complements this body of research by providing an empirical evaluation of the degree of association between runtime properties and class-level testability in object-oriented (OO) systems. The motivation for the use of dynamic code properties comes from the success of such metrics in providing a more complete insight into the multiple dimensions of software quality. In particular, we investigate the potential relationships between the runtime characteristics of production code, represented by Dynamic Coupling and Key Classes, and internal class-level testability. Testability of a class is considered here at the level of unit tests and two different measures are used to characterise those unit tests. The selected measures relate to test scope and structure: one is intended to measure the unit test size, represented by test lines of code, and the other is designed to reflect the intended design, represented by the number of test cases. In this research we found that Dynamic Coupling and Key Classes have significant correlations with class-level testability measures. We therefore suggest that these properties could be used as indicators of class-level testability. These results enhance our current knowledge and should help researchers in the area to build on previous results regarding factors believed to be related to testability and testing. Our results should also benefit practitioners in future class testability planning and maintenance activities.
Supervised Learning Based Power Management for Multicore Processors

This paper presents a supervised learning based power management framework for a multi-processor system, where a power manager (PM) learns to predict the system performance state from some readily available input features (such as the occupancy state of a global service queue) and then uses this predicted state to look up the optimal power management action (e.g., voltage-frequency setting) from a precomputed policy table. The motivation for utilizing supervised learning in the form of a Bayesian classifier is to reduce the overhead of the PM which has to repetitively determine and assign voltage-frequency settings for each processor core in the system. Experimental results demonstrate that the proposed supervised learning based power management technique ensures system-wide energy savings under rapidly and widely varying workloads.
A functional drug re-purposing screening identifies carfilzomib as a drug preventing 17β-estradiol: ERα signaling and cell proliferation in breast cancer cells

Most cases of breast cancer (BC) are estrogen receptor α-positive (ERα+) at diagnosis. The presence of ERα drives the therapeutic approach for this disease, which often consists of endocrine therapy (ET). 4OH-Tamoxifen and faslodex (i.e., fulvestrant - ICI182,780) are two ETs that render tumor cells insensitive to 17β-estradiol (E2)-dependent proliferative stimuli and prevent BC progression. However, ET has limitations and serious failures in different tissues and organs. Thus, there is an urgent need to identify novel drugs to fight BC in the clinic. Re-positioning of old drugs for new clinical purposes is an attractive alternative for drug discovery. For this analysis, we focused on the modulation of intracellular ERα levels in BC cells as target for the screening of about 900 Food and Drug Administration (FDA) approved compounds that would hinder E2:ERα signaling and inhibit BC cell proliferation. We found that carfilzomib induces ERα degradation and prevents E2 signaling and cell proliferation in two ERα+ BC cell lines. Remarkably, the analysis of carfilzomib effects on a cell model system with an acquired resistance to 4OH-tamoxifen revealed that this drug has an antiproliferative effect superior to faslodex in BC cells. Therefore, our results identify carfilzomib as a drug preventing E2:ERα signaling and cell proliferation in BC cells and suggest its possible re-position for the treatment of ERα+ BC as well as for those diseases that have acquired resistance to 4OH-tamoxifen.
Inductive Transfer Deep Hashing for Image Retrieval

With the explosive increase of online images, fast similarity search is increasingly critical for large scale image retrieval. Several hashing methods have been proposed to accelerate image retrieval, a promising way is semantic hashing which designs compact binary codes for a large number of images so that semantically similar images are mapped to similar codes. Supervised methods can handle such semantic similarity but they are prone to overfitting when the labeled data is few or noisy. In this paper, we concentrate on this issue and propose a novel Inductive Transfer Deep Hashing (ITDH) approach for semantic hashing based image retrieval. A transfer deep learning algorithm has been employed to learn the robust image representation, and the neighborhood-structure preserved method has been used to mapped the image into discriminative hash codes in hamming space. The combination of the two techniques ensures that we obtain a good feature representation and a fast query speed without depending on large amounts of labeled data. Experimental results demonstrate that the proposed approach is superior to some state-of-the-art methods.
The Distributional Preferences of Americans

We measure the distributional preferences of a large, diverse sample of Americans by embedding modified dictator games that vary the relative price of redistribution in the American Life Panel. Subjects' choices are generally consistent with maximizing a (social) utility function. We decompose distributional preferences into two distinct components - fair-mindedness (tradeoffs between oneself and others) and equality-efficiency tradeoffs - by estimating constant elasticity of substitution utility functions at the individual level. Approximately equal numbers of Americans have equality-focused and efficiency-focused distributional preferences. After controlling for individual characteristics, our experimental measures of equality-efficiency tradeoffs predict the political decisions of our subjects.
A constrained clustering based approach for matching a collection of feature sets

We consider the problem of finding feature correspondences among a collection of feature sets, by using point-wise unary features. This is fundamental in computer vision and pattern recognition, which also relates to areas e.g. operational research. Different from two-set matching which can be transformed to a quadratic assignment programming task that is known NP-hard, inclusion of merely unary attributes leads to a linear assignment problem. This problem has been well studied and there are effective polynomial global optimum solvers such as the Hungarian method. However, it becomes ill-posed when the unary attributes are (heavily) corrupted. The global optimal correspondence concerning the best score defined by the attribute affinity/cost between the two sets can be distinct to the ground truth correspondence since the score function is biased by noises. To combat this issue, we devise a method for matching a collection of feature sets by synergetically exploring the information across the sets. In general, our method can be perceived from a (constrained) clustering perspective: in each iteration, it assigns the features of one set to the clusters formed by the rest of feature sets, and updates the cluster centers in turn. Results on both synthetic data and real images suggest the efficacy of our method against state-of-the-arts.
Framework and challenges for Wireless body area networks based on big data

Big Data is a concept proposed on the basis of cloud computing, referring to the large-scale distributed data processing applications that operate on exceptionally large amounts of data. Wireless body area network (WBAN) is a dynamic network with sensor nodes in, on or around the body to monitor the physical parameters. The data of these parameters is so large which we called WBAN big data that traditional methods can not process them efficiently. In this paper, we propose the overall WBAN big data processing framework, and apply MapReduce and HBase to process, store and update the WBAN big data. Two problems of WBAN big data: Interfence and storage are investigated. Taking the specific feathers of WBAN big data into consideration, the framework will satisfy the goal of processing big data in WBAN and achieve the reasonable results that we hope.
The Cerebellum and English Grammatical Morphology: Evidence from Production, Comprehension, and Grammaticality Judgments

Three neuropsychological experiments on a group of 16 cerebellar patients and 16 age-and education-matched controls investigated the effects of damage to the cerebellum on English grammatical morphology across production, comprehension, and grammaticality judgment tasks. In Experiment 1, participants described a series of pictures previously used in studies of cortical aphasic patients. The cerebellar patients did not differ significantly from the controls in the total number of words produced or in the proportion of closed-class words. They did differ to a marginally significant extent in the production of required articles. In Experiment 2, participants identified the agent in a series of aurally presented sentences in which three agency cues (subjectverb agreement, word order, and noun animacy) were manipulated. The cerebellar patients were less affected than the controls were by the manipulation of subjectverb agreement to a marginally significant extent. In Experiment 3, participants performed a grammaticality judgment task on a series of aurally presented sentences. The cerebellar patients were significantly less able to discriminate grammatical and ungrammatical sentences than the controls were, particularly when the error was of subject verb agreement as opposed to word order. The results suggest that damage to the cerebellum can result in subtle impairments in the use of grammatical morphology, and are discussed in light of hypothesized roles for the cerebellum in language.