Miracle-dz/UniFAR-FTUs huggingface dataset:
Drug Repurposing to Fight Colistin and Carbapenem-Resistant Bacteria

The emergence of new resistance mechanisms, the failure of classical antibiotics in clinic, the decrease in the development of antibiotics in the industry are all challenges that lead us to consider new strategies for the treatment of infectious diseases. Indeed, in recent years controversy has intensified over strains resistant to carbapenem and/or colistin. Various therapeutic solutions are used to overcome administration of last line antibiotics. In this context, drug repurposing, which consists of using a non-antibiotic compound to treat multi-drug resistant bacteria (MDR), is encouraged. In this review, we first report what may have led to drug repurposing. Main definitions, advantages and drawbacks are summarized. Three major methods are described: phenotypic, computational and serendipity. In a second time we will focus on the current knowledge in drug repurposing for carbapenem and colistin-resistant bacteria with different studies describing repurposed compounds tested on Gram-negative bacteria. Furthermore, we show that drug combination therapies can increase successful by drug repurposing strategy. In conclusion, we discuss the pharmaceutical industries that have little interest in reprofiling drugs due to lack of profits. We also consider what a clinician might think of the indications of these uncommon biologists to treat MDR bacterial infections and avoid therapeutic impasses.
Can Sense of Opportunity Identification Efficacy Play a Mediating Role? Relationship Between Network Embeddedness and Social Entrepreneurial Intention of University Students

Social entrepreneurship is an entrepreneurial activity centering on solving social problems and creating social values, which can effectively alleviate the problems of sustainable development such as an excessive gap between the rich and the poor, a lack of resources and so on, and can resolve the “triple failures” of government, the market and public welfare departments to a certain extent. As the subjective attitude of entrepreneurs, entrepreneurial intention can predict a representational incidence rate of entrepreneurial behavior. Therefore, aimed at university students, a special group of entrepreneurs, this paper constructs a theoretical framework of “network embeddedness – sense of opportunity identification efficacy – university students’ social entrepreneurial intention” from the perspective of social cognitive theory through 466 pieces of valid survey data, and uses Stata 14 to construct a multiple linear regression model to explore the mechanism of action between the three. The results show that university students’ sense of opportunity identification efficacy can significantly and positively stimulate their social entrepreneurial intention, and the network embeddedness (network scale and network intensity) of entrepreneurs is also significantly and positively correlated with their sense of opportunity identification efficacy; however, via the hierarchical regression model, it was found that the sense of opportunity identification efficacy can only partially mediate the relationship between network embeddedness and university students’ social entrepreneurial intention, which is mainly manifested in the positive correlation between university students’ social entrepreneurial intention and their network scale, and is unrelated to network intensity. This research contributes to enriching the theory of social entrepreneurial intention and guides the strengthening of university students’ social entrepreneurial intention in reality.
Clinical Presentations and Outcomes Related to Tuberculosis in Children Younger Than 2 Years of Age in Catalonia

Introduction: Children younger than 2 years have an increased risk of complications associated with tuberculosis (TB) due to the immaturity of the innate and adaptive immune response. We aimed to identify TB clinical presentations and outcomes as well as risk factors for complications in this age group. Materials and Methods: Multicenter, retrospective, cross-sectional study of TB cases in children aged <2 years in Catalonia (2005–2013). Epidemiological and clinical data were collected from the hospital medical records. TB complications, sequelae included, were defined as any tissue damage generating functional or anatomical impairment after being diagnosed or after TB treatment being completed. Statistical analyses were based on bivariate chi-square and multivariate logistic regression, and it was carried out with Stata® version 13.1. Odds ratios (OR) and its 95% confidence intervals were calculated (CI). Results: A total of 134 patients were included, 50.7% were male, the median [IQR] age was 13[8-18] months, and 18.7% (25/134) showed TB-associated complications. Pulmonary TB was diagnosed in 94.0% (126/134) of children, and the most common complications were lobar collapse (6/126). TB meningitis was diagnosed in 14/134 (10.4%), and hydrocephalus and mental impairment occurred in 1 and 2 patients, respectively. Two patients with spinal TB developed vertebral destruction and paraplegia, respectively. Only one of the patients died. At multivariate level, tachypnea (OR = 4.24; 95% CI 1.17–15.35) and meningeal (OR = 52.21; 95% CI 10.05–271.2) or combined/extrapulmonary forms (OR = 11.3; 95% CI 2.85–45.1) were associated with the development of TB complications. Discussion: TB complications are common in children under 2 years old. Extrapulmonary TB forms in this pediatric age remain a challenge and require prompt diagnosis and treatment in order to prevent them. The presence of tachypnea at the time of TB diagnosis is an independent associated factor to the development of TB complications in infants. This clinical sign should be closely monitored in patients in this age group. It is necessary to perform further studies in this age group in a prospective design in order to understand whether there are other factors associated to TB complications.
Stability problems in nonautonomous linear differential equations in infinite dimensions

One goal of this paper is to study robustness of stability of nonautonomous linear ordinary differential equations under integrally small perturbations in an infinite dimensional Banach space. Some applications are obtained to the case of rapid oscillatory perturbations, with arbitrary small periods, showing that even in this case the stability is robust. These results extend to infinite dimensions some results given in Coppel (1970). Based in Rodrigues (1970) and in Kloeden and Rodrigues (2011) we introduce a class of functions that we call Generalized Almost Periodic Functions that extend the usual almost periodic functions and are suitable to deal with oscillatory perturbations. We also present an infinite dimensional example of the previous results. We show in another example that it is possible to stabilize an unstable system using a perturbation with large period and small mean value. Finally, we give an example where we stabilize an unstable linear ODE with small perturbation in infinite dimensions using some ideas developed in Rodrigues andSola-Morales (2019)} and in an example of Kakutani, see Rickard (1960).
Ketone Bodies in Neurological Diseases: Focus on Neuroprotection and Underlying Mechanisms

There is growing evidence that ketone bodies, which are derived from fatty acid oxidation and usually produced in fasting state or on high-fat diets have broad neuroprotective effects. Although the mechanisms underlying the neuroprotective effects of ketone bodies have not yet been fully elucidated, studies in recent years provided abundant shreds of evidence that ketone bodies exert neuroprotective effects through possible mechanisms of anti-oxidative stress, maintaining energy supply, modulating the activity of deacetylation and inflammatory responses. Based on the neuroprotective effects, the ketogenic diet has been used in the treatment of several neurological diseases such as refractory epilepsy, Parkinson's disease, Alzheimer's disease, and traumatic brain injury. The ketogenic diet has great potential clinically, which should be further explored in future studies. It is necessary to specify the roles of components in ketone bodies and their therapeutic targets and related pathways to optimize the strategy and efficacy of ketogenic diet therapy in the future.
Proteomic De-Regulation in Cyanobacteria in Response to Abiotic Stresses

Cyanobacteria are oxygenic photoautotrophs, exhibiting a cosmopolitan distribution in almost all possible environments and are significantly responsible for half of the global net primary productivity. They are well adapted to the diverse environments including harsh conditions by evolving a range of fascinating repertoires of unique biomolecules and secondary metabolites to support their growth and survival. These phototrophs are proved as excellent models for unraveling the mysteries of basic biochemical and physiological processes taking place in higher plants. Several known species of cyanobacteria have tremendous biotechnological applications in diverse fields such as biofuels, biopolymers, secondary metabolites and much more. Due to their potential biotechnological and commercial applications in various fields, there is an imperative need to engineer robust cyanobacteria in such a way that they can tolerate and acclimatize to ever-changing environmental conditions. Adaptations to stress are mainly governed by a precise gene regulation pathways resulting in the expression of novel protein/enzymes and metabolites. Despite the demand, till date few proteins/enzymes have been identified which play a potential role in improving tolerance against abiotic stresses. Therefore, it is utmost important to study environmental stress responses related to post-genomic investigations, including proteomic changes employing advanced proteomics, synthetic and structural biology workflows. In this respect, the study of stress proteomics offers exclusive advantages to scientists working on these aspects. Advancements on these fields could be helpful in dissecting, characterization and manipulation of physiological and metabolic systems of cyanobacteria to understand the stress induced proteomic responses. Till date, it remains ambiguous how cyanobacteria perceive changes in the ambient environment that lead to the stress-induced proteins thus metabolic deregulation. This review briefly describes the current major findings in the fields of proteome research on the cyanobacteria under various abiotic stresses. These findings may improve and advance the information on the role of different class of proteins associated with the mechanism(s) of stress mitigation in cyanobacteria under harsh environmental conditions.
Whey Protein Supplementation Post Resistance Exercise in Elderly Men Induces Changes in Muscle miRNA's Compared to Resistance Exercise Alone

Progressive muscle loss with aging results in decreased physical function, frailty, and impaired metabolic health. Deficits in anabolic signaling contribute to an impaired ability for aged skeletal muscle to adapt in response to exercise and protein feeding. One potential contributing mechanism could be exerted by dysregulation of microRNAs (miRNAs). Therefore, the aim of this study was to determine if graded protein doses consumed after resistance exercise altered muscle miRNA expression in elderly men. Twenty-three senior men (67.9 ± 0.9 years) performed a bout of resistance exercise and were randomized to consume either a placebo, 20 or 40 g of whey protein (n = 8, n = 7, and n = 8, respectively). Vastus lateralis biopsies were collected before, 2 and 4 h after exercise. Expression of 19 miRNAs, previously identified to influence muscle phenotype, were measured via RT-PCR. Of these, miR-16-5p was altered with exercise in all groups (p = 0.032). Expression of miR-15a and-499a increased only in the placebo group 4 h after exercise and miR-451a expression increased following exercise only in the 40 g whey supplementation group. Changes in p-P70S6KThr389 and p-AktSer473 following exercise were correlated with alterations in miR-208a and-499a and-206 expression, irrespective of protein dose, suggesting a possible role for miRNA in the regulation of acute phosphorylation events during early hours of exercise recovery.
Chocolatine: Outage Detection for Internet Background Radiation

The Internet is a complex ecosystem composed of thousands of Autonomous Systems (ASs) operated by independent organizations; each AS having a very limited view outside its own network. These complexities and limitations impede network operators to finely pinpoint the causes of service degradation or disruption when the problem lies outside of their network. In this paper, we present Chocolatine, a solution to detect remote connectivity loss using Internet Background Radiation (IBR) through a simple and efficient method. IBR is unidirectional unsolicited Internet traffic, which is easily observed by monitoring unused address space. IBR features two remarkable properties: it is originated worldwide, across diverse ASs, and it is incessant. We show that the number of IP addresses observed from an AS or a geographical area follows a periodic pattern. Then, using Seasonal ARIMA to statistically model IBR data, we predict the number of IPs for the next time window. Significant deviations from these predictions indicate an outage. We evaluated Chocolatine using data from the UCSD Network Telescope, operated by CAIDA, with a set of documented outages. Our experiments show that the proposed methodology achieves a good trade-off between true-positive rate (90%) and falsepositive rate (2%) and largely outperforms CAIDA’s own IBR-based detection method. Furthermore, performing a comparison against other methods, i.e., with BGP monitoring and active probing, we observe that Chocolatine shares a large common set of outages with them in addition to many specific outages that would otherwise go undetected.
The binary millisecond pulsar PSR J1023+0038 – II. Optical spectroscopy

We present time-resolved optical spectroscopy of the ‘redback’ binary millisecond pulsar system PSR J1023+0038 during both its radio pulsar (2009) and accretion disc states (2014 and 2016). We provide observational evidence for the companion star being heated during the disc state. We observe a spectral type change along the orbit, from ∼G5 to ∼F6 at the secondary star’s superior and inferior conjunction, respectively, and find that the corresponding irradiating luminosity can be powered by the high-energy accretion luminosity or the spin-down luminosity of the neutron star. We determine the secondary star’s radial velocity semi-amplitude from the metallic (primarily Fe and Ca) and Hα absorption lines during these different states. The metallic and Hα radial velocity semi-amplitude determined from the 2009 pulsar-state observations allows us to constrain the secondary star’s true radial velocity K2 = 276.3 ± 5.6 km s−1 and the binary mass ratio q = 0.137 ± 0.003. By comparing the observed metallic and Hα absorption-line radial velocity semi-amplitudes with model predictions, we can explain the observed semi-amplitude changes during the pulsar state and during the pulsar/disc-state transition as being due to different amounts of heating and the presence of an accretion disc, respectively.
Overview Inflation and Inflation Targets

Johnson’s paper addresses one of the main issues of central banking: How successful have monetary authorities been in acquiring credibility for their inflation objectives? Johnson’s approach is both simple and elegant. For countries with explicit inflation targets, he examines whether inflation expectations are consistent with those targets. Since not all central banks have explicit inflation targets, he also asks whether inflation has been easily predictable, since this is viewed as one indicator of the successful implementation of monetary policy. The results, though mixed, are not particularly favourable for those countries with explicit inflation targets. Most countries that tried to establish “credible” inflation targets over the sample period failed, and inflation was in general no easier to predict in countries with targets than in those without.
Neural query expansion for code search

Searching repositories of existing source code for code snippets is a key task in software engineering. Over the years, many approaches to this problem have been proposed. One recent tool called NCS, takes in a natural language query and outputs relevant code snippets, often being able to correctly answer Stack Overflow questions. But what happens when the developer doesn’t provide a query with a clear intent? What if shorter queries are used to demonstrate a more vague intent? We find that the performance of NCS regresses with shorter queries. Furthermore, data from developers’ code search history logs shows that shorter queries have a less successful code search session: there are more query reformulations and more time is spent browsing the results. These observations lead us to believe that using NCS alone with short queries may not be productive enough. In this paper, we explore an additional way of using neural networks in code search: the automatic expansion of queries. We present NQE, a neural model that takes in a set of keywords and predicts a set of keywords to expand the query to NCS. NQE learns to predict keywords that co-occur with the query keywords in the underlying corpus, which helps expand the query in a productive way. Our results show that with query expansion, NQE + NCS is able to perform better than using NCS alone.
TeIL: a type-safe imperative tensor intermediate language

Each of the popular tensor frameworks from the machine learning domain comes with its own language for expressing tensor kernels. Since these tensor languages lack precise specifications, it is impossible to understand and reason about tensor kernels that exhibit unexpected behaviour. In this paper, we give examples of such kernels. The tensor languages are superficially similar to the well-known functional array languages, for which formal definitions often exist. However, the tensor languages are inherently imperative. In this paper we present TeIL, an imperative tensor intermediate language with precise formal semantics. For the popular tensor languages, TeIL can serve as a common ground on the basis of which precise reasoning about kernels becomes possible. Based on TeIL's formal semantics we develop a type-safety result in the Coq proof assistant.
Dynamic Regulation of the 26S Proteasome: From Synthesis to Degradation

All eukaryotes rely on selective proteolysis to control the abundance of key regulatory proteins and maintain a healthy and properly functioning proteome. Most of this turnover is catalyzed by the 26S proteasome, an intricate, multi-subunit proteolytic machine. Proteasomes recognize and degrade proteins first marked with one or more chains of poly-ubiquitin, the addition of which is actuated by hundreds of ligases that individually identify appropriate substrates for ubiquitylation. Subsequent proteasomal digestion is essential and influences a myriad of cellular processes in species as diverse as plants, fungi and humans. Importantly, dysfunction of 26S proteasomes is associated with numerous human pathologies and profoundly impacts crop performance, thus making an understanding of proteasome dynamics critically relevant to almost all facets of human health and nutrition. Given this widespread significance, it is not surprising that sophisticated mechanisms have evolved to tightly regulate 26S proteasome assembly, abundance and activity in response to demand, organismal development and stress. These include controls on transcription and chaperone-mediated assembly, influences on proteasome localization and activity by an assortment of binding proteins and post-translational modifications, and ultimately the removal of excess or damaged particles via autophagy. Intriguingly, the autophagic clearance of damaged 26S proteasomes first involves their modification with ubiquitin, thus connecting ubiquitylation and autophagy as key regulatory events in proteasome quality control. This turnover is also influenced by two distinct biomolecular condensates that coalesce in the cytoplasm, one attracting damaged proteasomes for autophagy, and the other reversibly storing proteasomes during carbon starvation to protect them from autophagic clearance. In this review, we describe the current state of knowledge regarding the dynamic regulation of 26S proteasomes at all stages of their life cycle, illustrating how protein degradation through this proteolytic machine is tightly controlled to ensure optimal growth, development and longevity.
Piecewise isometries, uniform distribution and 3log 2−π2/8

Abstract We use analytic tools to study a simple family of piecewise isometries of the plane parameterized by an angle. In previous work, we showed the existence of large numbers of periodic points, each surrounded by a ‘periodic island’. We also proved conservativity of the systems as infinite measure-preserving transformations. In experiments it is observed that the periodic islands fill up a large part of the phase space and it has been asked whether the periodic islands form a set of full measure. In this paper we study the periodic islands around an important family of periodic orbits and demonstrate that for all angle parameters that are irrational multiples of π, the islands have asymptotic density in the plane of 3log 2−π2/8≈0.846.
A matrix analysis of functional centrality measures

We consider a broad class of walk-based, parameterized node centrality measures for network analysis. These measures are expressed in terms of functions of the adjacency matrix and generalize various well-known centrality indices, including Katz and subgraph centrality. We show that the parameter can be “tuned” to interpolate between degree and eigenvector centrality, which appear as limiting cases. Our analysis helps explain certain correlations often observed between the rankings obtained using different centrality measures, and provides some guidance for the tuning of parameters. We also highlight the roles played by the spectral gap of the adjacency matrix and by the number of triangles in the network. Our analysis covers both undirected and directed networks, including weighted ones. A brief discussion of PageRank is also given.
ADAPTIVE KERNEL SELF-ORGANIZING MAPS USING INFORMATION THEORETIC LEARNING

of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ADAPTIVE KERNEL SELF-ORGANIZING MAPS USING INFORMATION THEORETIC LEARNING By Rakesh Chalasani May 2010 Chair: José Carlos Prı́ncipe Major: Electrical and Computer Engineering Self organizing map (SOM) is one of the popular clustering and data visualization algorithm and evolved as a useful tool in pattern recognition, data mining, etc., since it was first introduced by Kohonen. However, it is observed that the magnification factor for such mappings deviates from the information theoretically optimal value of 1 (for the SOM it is 2/3). This can be attributed to the use of the mean square error to adapt the system, which distorts the mapping by over sampling the low probability regions. In this work, the use of a kernel based similarity measure called correntropy induced metric (CIM) for learning the SOM is proposed and it is shown that this can enhance the magnification of the mapping without much increase in the computational complexity of the algorithm. It is also shown that adapting the SOM in the CIM sense is equivalent to reducing the localized cross information potential and hence, the adaptation process as a density estimation procedure. A kernel bandwidth adaptation algorithm in case of the Gaussian kernels, for both homoscedastic and heteroscedastic components, is also proposed using this property.