Miracle-dz/UniFAR-FTUs huggingface dataset:
Ticks and Tularemia: Do We Know What We Don't Know?

Francisella tularensis, the causative agent of the zoonotic disease tularemia, is characterized by high morbidity and mortality rates in over 190 different mammalian species, including humans. Based on its low infectious dose, multiple routes of infection, and ability to induce rapid and lethal disease, F. tularensis has been recognized as a severe public health threat—being designated as a NIH Category A Priority Pathogen and a CDC Tier 1 Select Agent. Despite concerns over its use as a bioweapon, most U.S. tularemia cases are tick-mediated and ticks are believed to be the major environmental reservoir for F. tularensis in the U.S. The American dog tick (Dermacentor variabilis) has been reported to be the primary tick vector for F. tularensis, but the lone star tick (Amblyomma americanum) and other tick species also have been shown to harbor F. tularensis. This review highlights what is known, not known, and is debated, about the roles of different tick species as environmental reservoirs and transmission vectors for a variety of F. tularensis genotypes/strains.
Encoding Social Interactions: The Neural Correlates of True and False Memories

In social situations, we encounter information transferred in firsthand (egocentric) and secondhand (allocentric) communication contexts. However, the mechanism by which an individual distinguishes whether a past interaction occurred in an egocentric versus allocentric situation is poorly understood. This study examined the neural bases for encoding memories of social interactions through experimentally manipulating the communication context. During fMRI data acquisition, participants watched video clips of an actor speaking and gesturing directly toward them (egocentric context) or toward an unseen third person (allocentric context). After scanning, a recognition task gauged participants' ability to recognize the sentences they had just seen and to recall the context in which the sentences had been spoken. We found no differences between the recognition of sentences spoken in egocentric and allocentric contexts. However, when asked about the communication context (“Had the actor directly spoken to you? ”), participants tended to believe falsely that the actor had directly spoken to them during allocentric conditions. Greater activity in the hippocampus was related to correct context memory, whereas the ventral ACC was activated for subsequent inaccurate context memory. For the interaction between encoding context and context memory, we observed increased activation for egocentric remembered items in the bilateral and medial frontal cortex, the BG, and the left parietal and temporal lobe. Our data indicate that memories of social interactions are biased to be remembered egocentrically. Self-referential encoding processes reflected in increased frontal activation and decreased hippocampal activation might be the basis of correct item but false context memory of social interactions.
The Shallow End: Empowering Shallower Deep-Convolutional Networks through Auxiliary Outputs

Depth is one of the key factors behind the success of convolutional neural networks (CNNs). Since ResNet, we are able to train very deep CNNs as the gradient vanishing issue has been largely addressed by the introduction of skip connections. However, we observe that, when the depth is very large, the intermediate layers (especially shallow layers) may fail to receive sufficient supervision from the loss due to the severe transformation through a long backpropagation path. As a result, the representation power of intermediate layers can be very weak and the model becomes very redundant with limited performance. In this paper, we first investigate the supervision vanishing issue in existing backpropagation (BP) methods. And then, we propose to address it via an effective method, called Multi-way BP (MW-BP), which relies on multiple auxiliary losses added to the intermediate layers of the network. The proposed MW-BP method can be applied to most deep architectures with slight modifications, such as ResNet and MobileNet. Our method often gives rise to much more compact models (denoted by "Mw+Architecture") than existing methods. For example, MwResNet-44 with 44 layers performs better than ResNet-110 with 110 layers on CIFAR-10 and CIFAR-100. More critically, the resultant models even outperform the light models obtained by state-of-the-art model compression methods. Last, our method inherently produces multiple compact models with different depths at the same time, which is helpful for model selection.
MULTINATIONAL FIRMS AND KNOWLEDGE DIFFUSION: EVIDENCE USING PATENT CITATION DATA

To understand the role of MNCs in international knowledge diffusion, two questions need to be considered: (1) How actively do overseas subsidiaries of an MNC exchange knowledge with other players in the host country? (2) To what extent do these overseas MNC subsidiaries facilitate bi-directional knowledge flows between the MNC home base and the host country? To address these issues, I analyze citation patterns for over half a million patents from 4,400 firms and organizations across six countries and all manufacturing sectors. I estimate the probability of individual knowledge flows using a weighted maximum likelihood approach for choice-based samples. My overall results suggest that there are significant bi-directional knowledge flows between MNCs and their host countries, but MNCs contribute less to host country knowledge than they gain from it. For knowledge flows within host countries: (1a)Knowledge flows from domestic entities to MNC subsidiaries are as strong as those between domestic entities; (1b).
Multiscale poromechanics of wet cement paste

Significance Capillary effects in cement paste are associated with multiple degradation mechanisms. Using a framework, we investigated the role of capillary forces in cement paste under partial saturation from the nanograins level to the mesoscale. We show that the largest capillary forces concentrate at the boundary between gel pores and larger capillary pores, inducing nonaffine deformations with correlations up to a few tens of nanometers. Our results suggest a homogenization length scale common to liquid and solid stresses correlated with the scale of inherent structural heterogeneities. This opens the route to studying the poromechanics of complex multiscale media with explicit fluid–solid coupling. Capillary effects, such as imbibition drying cycles, impact the mechanics of granular systems over time. A multiscale poromechanics framework was applied to cement paste, which is the most common building material, experiencing broad humidity variations over the lifetime of infrastructure. First, the liquid density distribution at intermediate to high relative humidity is obtained using a lattice gas density functional method together with a realistic nanogranular model of cement hydrates. The calculated adsorption/desorption isotherms and pore size distributions are discussed and compare well with nitrogen and water experiments. The standard method for pore size distribution determination from desorption data is evaluated. Second, the integration of the Korteweg liquid stress field around each cement hydrate particle provided the capillary forces at the nanoscale. The cement mesoscale structure was relaxed under the action of the capillary forces. Local irreversible deformations of the cement nanograins assembly were identified due to liquid–solid interactions. The spatial correlations of the nonaffine displacements extend to a few tens of nanometers. Third, the Love–Weber method provided the homogenized liquid stress at the micrometer scale. The homogenization length coincided with the spatial correlation length of nonaffine displacements. Our results on the solid response to capillary stress field suggest that the micrometer-scale texture is not affected by mild drying, while nanoscale irreversible deformations still occur. These results pave the way for understanding capillary phenomena-induced stresses in heterogeneous porous media ranging from construction materials to hydrogels and living systems.
Saturated Fat Intake and Insulin Resistance in Men With Coronary Artery Disease

Background To determine whether there is an association between diet and plasma insulin concentration that is independent of obesity, we studied the relation of dietary composition and caloric intake to obesity and plasma insulin concentrations in 215 nondiabetic men aged 32–74 years with angiographically proven coronary artery disease. Methods and Results After adjusting for age, the intake of saturated fatty acids and cholesterol were positively correlated (p < 0.05) with body mass index (r = 0.18, r = 0.16), waist-to-hip circumference ratio (r = 0.21, r = 0.22), and fasting insulin (r = 0.26, r = 0.23). Carbohydrate intake was negatively correlated with body mass index (r = −0.21), waist-to-hip ratio (r = −0.21), and fasting insulin (r = −0.16). Intake of monounsaturated fatty acids did not correlate significantly with body mass index or waist-to-hip circumference ratio but did correlate positively with fasting insulin (r = 0.24). Intake of dietary calories was negatively correlated with body mass index (r = −0.15). In multivariate analysis, intake of saturated fatty acids was significantly related to elevated fasting insulin concentration independently of body mass index. Conclusions These cross-sectional findings in nondiabetic men with coronary artery disease suggest that increased consumption of saturated fatty acids is associated independently with higher fasting insulin concentrations.
Analysis of the Italian generic medicines retail market: recommendations to enhance long-term sustainability

Italy is among the European countries with the lowest uptake of generic medicines. This paper provides a perspective on the Italian generic medicines retail market. Fast market entrance of generic medicines in Italy is hindered by several factors: the existence of Complementary Protection Certificates in the past, the large market for copies and multiple cases of patent linkage. Prices of generic medicines in Italy are low compared to other European countries. To contain pharmaceutical expenditure, pharmaceutical companies are currently forced to pay back in case of overspending, which disproportionally penalizes small and fast growing companies, to which most generic companies belong to. Current demand-side policies do not successfully stimulate the use of generic medicines. The current market environment surrounding the Italian generic medicines retail market (i.e., low prices, low volumes) threatens its long-term sustainability. Recommendations to enhance the long-term sustainability of the Italian generic medicines retail market round off this perspective paper.
Growth and Poverty in Maharashtra

Maharashtra is among the richest states in India in terms of per capita income, yet incidence of poverty in the state remains close to the national average. The states economy grew at a faster rate than the all-India average during 1980-1 to 1992-3, but it slowed down a bit during 1993-4 to 2003-4 due to poorer performance of agriculture and industry. Agricultures contribution to GSDP has come down to 12 per cent in 2002-3, but more than 50 per cent of total workers are still engaged in this. Cropping pattern has been shifting to greater value addition non-cereal crops like fruits, vegetables, oilseeds and sugarcane. Composition of manufacturing has shifted towards more capital-intensive sectors. Communication, transport and public administration have accounted for large part of service growth. The benefits of this growth process have, however, not spread equally across social groups or regions, which partly explains prevalence of high poverty compared to other states at similar mean income. The much talked about Maharashtra Employment Guarantee Scheme (MEGS) has had limited success and its coverage across districts/divisions is not proportionate to the share of poor. Despite these developments, rural poverty has reduced from 38 per cent in 1993-4 to around 24 per cent in 1999-2000. Given current investment flows, the overall growth potential of Maharashtra does look bright for the medium run. But, distributional implications of the emerging growth pattern across sectors suggest that the poor might not benefit proportionately from the growth process. The lessons that Maharashtra provides is that growth has to be more broad-based and inclusive, and that intervention through social welfare programmes like MEGS should be designed to suit the local resource base of poorer regions for faster poverty reduction.
Countercyclical Elasticity of Substitution

We empirically show that the short-run elasticity of substitution between capital and labor (? t) is countercyclical. In recessions, capital and labor are more substitutable than in expansions. We explore the effects of the countercyclicality of ? t on aggregate fluctuations in the context of an otherwise standard competitive-markets business cycle model. The countercyclical ? t contributes to resolve four main labor-market puzzles: Dunlop-Tarshis phenomenon, labor-productivity puzzle, hours-productivity puzzle, and labor share puzzle.
Expression of CD5 and CD38 by human CD5− B cells: Requirement for special stimuli

In this study the mode of expression of CD5 by human tonsillar CD5− B cells after stimulation with different agents was investigated. Resting B cells were separated into CD5+ and CD5− cells and the two cell fractions exposed to phorbol 12‐myristate 13‐acetate (PMA). CD5− B cells expressed CD5 and maximum CD5 expression was achieved after approximately 60 h of culture. Based upon the proportions of cells that express CD5 as well as those of the cells surviving in culture, it was calculated that 15–25 % of the total CD5− B cells were induced to express CD5. Unlike CD5− B cells, CD5+ B cells proliferated vigorously in response to PMA as assessed by [3H] thymidine incorporation and cell cycle analysis in vitro. However, the expression of CD5 by CD5− B cells was not related to the selective expansion of some CD5+ B cells left over as contaminant cells since this occurred in the absence of cell proliferation. Upon exposure to PMA, CD5− B cells remained in the G0‐G1 phases of the cell cycle and did not express the Ki67 antigen or incorporate [3H] thymidine. Furthermore, mitomycin C treatment of the CD5− B cells did not prevent CD5 expression. Phenotypic studies disclosed that CD5+ B cells but not CD5− B cells expressed CD39. This finding offered the opportunity to carry out an additional control experiment. Separation of the two populations according to the expression of CD39 confirmed the finding obtained by fractionating the cells into CD5+ and CD5− B cells. The cells induced to express CD5 also expressed CD38 that was not detected on resting CD5− B cells. In this respect, the CD5− B cells that converted into CD5+ cells (inducible CD5+ B cells) resembled the cells from the CD5+ B cell fractions that up‐regulated CD5 and also expressed CD38 upon exposure to PMA alone. Another example of coordinate expression of these two antigens was the finding that exposure to PMA in the presence of recombinant interleukin‐4 (rIL‐4) resulted in inhibition of the expression of CD5 and CD38. Although virtually all of the tonsillar CD5− B cells expressed the CD69 activation marker, no cells other than those co‐expressing CD5 and CD38 were induced to express CD5 by PMA alone. Resting CD5− B cells failed to express CD5 and/or CD38 when cultured with PMA in the presence of EL4 T cells and IL‐4‐free T cell supernatants. Although this combination of stimuli induced a vigorous cell proliferation, the failure to express CD5 and CD38 was not related to cell cycling, since mitomicyn C‐treated CD5− B cells also failed to express CD5 or CD38 when exposed to PMA in the presence of EL4 cells with or without T cell supernatants. Thus, exposure to T cells alone was sufficient to down‐regulate CD5 and CD38 expression. Collectively, the above findings indicate that mature CD5− B cells can follow distinct pathways of differentiation depending upon the nature of the stimuli encountered, and that CD5 expression may identify a special B cell subset or a particular stage of B cell differentiation.
Syntactic priming in comprehension: the role of argument order and animacy.

Two visual-world eye-movement experiments investigated the nature of syntactic priming during comprehension--specifically, whether the priming effects in ditransitive prepositional object (PO) and double object (DO) structures (e.g., "The wizard will send the poison to the prince/the prince the poison? ") are due to anticipation of structural properties following the verb (send) in the target sentence or to anticipation of animacy properties of the first postverbal noun. Shortly following the target verb onset, listeners looked at the recipient more (relative to the theme) following DO than PO primes, indicating that the structure of the prime affected listeners' eye gazes on the target scene. Crucially, this priming effect was the same irrespective of whether the postverbal nouns in the prime sentences did ("The monarch will send the painting to the president") or did not ("The monarch will send the envoy to the president") differ in animacy, suggesting that PO/DO priming in comprehension occurs because structural properties, rather than animacy features, are being primed when people process the ditransitive target verb.
Adversarial Networks-Based Speech Enhancement with Deep Regret Loss

Speech enhancement is often applied for speech-based systems due to the proneness of speech signals to additive background noise. While speech processing-based methods are traditionally used for speech enhancement, with advancements in deep learning technologies, many efforts have been made to implement them for speech enhancement. Using deep learning, the networks learn mapping functions from noisy data to clean ones and then learn to reconstruct the clean speech signals. As a consequence, deep learning methods can reduce what is so-called musical noise that is often found in traditional speech enhancement methods. Currently, one popular deep learning architecture for speech enhancement is generative adversarial networks (GAN). However, the cross-entropy loss that is employed in GAN often causes the training to be unstable. So, in many implementations of GAN, the cross-entropy loss is replaced with the least-square loss. In this paper, to improve the training stability of GAN using cross-entropy loss, we propose to use deep regret analytic generative adversarial networks (Dragan) for speech enhancements. It is based on applying a gradient penalty on cross-entropy loss. We also employ relativistic rules to stabilize the training of GAN. Then, we applied it to the least square and Dragan losses. Our experiments suggest that the proposed method improve the quality of speech better than the least-square loss on several objective quality metrics.
Caractérisations des modèles multivariés de stables-Tweedie multiples

Ce travail de these porte sur differentes caracterisations des modeles multivaries de stables-Tweedie multiples dans le cadre des familles exponentielles naturelles sous la propriete de "steepness". Ces modeles parus en 2014 dans la litterature ont ete d’abord introduits et decrits sous une forme restreinte des stables-Tweedie normaux avant les extensions aux cas multiples. Ils sont composes d’un melange d’une loi unidimensionnelle stable-Tweedie de variable reelle positive fixee, et des lois stables-Tweedie de variables reelles independantes conditionnees par la premiere fixee, de meme variance egale a la valeur de la variable fixee. Les modeles stables-Tweedie normaux correspondants sont ceux du melange d’une loi unidimensionnelle stable-Tweedie positive fixe et les autres toutes gaussiennes independantes. A travers des cas particuliers tels que normal, Poisson, gamma, inverse gaussienne, les modeles stables-Tweedie multiples sont tres frequents dans les etudes de statistique et probabilites appliquees. D’abord, nous avons caracterise les modeles stables-Tweedie normaux a travers leurs fonctions variances ou matrices de covariance exprimees en fonction de leurs vecteurs moyens. La nature des polynomes associes a ces modeles est deduite selon les valeurs de la puissance variance a l’aide des proprietes de quasi orthogonalite, des systemes de Levy-Sheffer, et des relations de recurrence polynomiale. Ensuite, ces premiers resultats nous ont permis de caracteriser a l’aide de la fonction variance la plus grande classe des stables-Tweedie multiples. Ce qui a conduit a une nouvelle classification laquelle rend la famille beaucoup plus comprehensible. Enfin, une extension de caracterisation des stables-Tweedie normaux par fonction variance generalisee ou determinant de la fonction variance a ete etablie via leur propriete d’indefinie divisibilite et en passant par les equations de Monge-Ampere correspondantes. Exprimees sous la forme de produit des composantes du vecteur moyen aux puissances multiples, la caracterisationde tous les modeles multivaries stables-Tweedie multiples par fonction variance generalisee reste un probleme ouvert.
Multi-Drug Resistance in Bacterial Genomes—A Comprehensive Bioinformatic Analysis

Antimicrobial resistance is presently one of the greatest threats to public health. The excessive and indiscriminate use of antibiotics imposes a continuous selective pressure that triggers the emergence of multi-drug resistance. We performed a large-scale analysis of closed bacterial genomes to identify multi-drug resistance considering the ResFinder antimicrobial classes. We found that more than 95% of the genomes harbor genes associated with resistance to disinfectants, glycopeptides, macrolides, and tetracyclines. On average, each genome encodes resistance to more than nine different classes of antimicrobial drugs. We found higher-than-expected co-occurrences of resistance genes in both plasmids and chromosomes for several classes of antibiotic resistance, including classes categorized as critical according to the World Health Organization (WHO). As a result of antibiotic-resistant priority pathogens, higher-than-expected co-occurrences appear in plasmids, increasing the potential for resistance dissemination. For the first time, co-occurrences of antibiotic resistance have been investigated for priority pathogens as defined by the WHO. For critically important pathogens, co-occurrences appear in plasmids, not in chromosomes, suggesting that the resistances may be epidemic and probably recent. These results hint at the need for new approaches to treating infections caused by critically important bacteria.