Miracle-dz/UniFAR-FTUs huggingface dataset:
PaMiraXT: Parallel SAT Solving with Threads and Message Passing

This article describes PaMiraXT, a powerful parallel SAT algorithm. PaMiraXT follows a master/client model based on message passing, making it suitable for any kind of workstation cluster. For the clients, MiraXT is used, which itself is thread-based parallel solver designed to take advantage of current and future shared memory multiprocessor systems. We highlight design and implementation details that allow the threads/clients to run and cooperate efficiently. Experimental results show that MiraXT compares well to other state-of-the-art SAT algorithms. In single-threaded mode, it outperforms MiniSat2, PicoSAT 535, and RSat 2.01, while in multi-threaded mode, MiraXT provides cutting edge performance, as it solves significantly more instances within the given time limit. A case study, using three copies of MiraXT with a total of 8 threads as clients, underlines the potential of PaMiraXT, resulting in a speedup of 5.62 on the industrial benchmarks of the 2007 SAT competition.
Practice of Epidemiology Using the Whole Cohort in the Analysis of Case-Cohort Data

Case-cohort data analyses often ignore valuable information on cohort members not sampled as cases or controls. The Atherosclerosis Risk in Communities (ARIC) study investigators, for example, typically report data for just the 10%–15% of subjects sampled for substudies of their cohort of 15,972 participants. Remaining subjects contribute to stratified sampling weights only. Analysis methods implemented in the freely available R statistical system (http://cran.r-project.org/) make better use of the data through adjustment of the sampling weights via calibration or estimation. By reanalyzing data from an ARIC study of coronary heart disease and simulations based on data from the National Wilms Tumor Study, the authors demonstrate that such adjustment can dramatically improve the precision of hazard ratios estimated for baseline covariates known for all subjects. Adjustment can also improve precision for partially missing covariates, those known for substudy participants only, when their values may be imputed with reasonable accuracy for the remaining cohort members. Links are provided to software, data sets, and tutorials showing in detail the steps needed to carry out the adjusted analyses. Epidemiologists are encouraged to consider use of these methods to enhance the accuracy of results reported from case-cohort analyses.
The special deep neural network for stationary signal spectra classification

A special deep neural network architecture for automatic classification of stationary signal spectra and the method of its training by precedents are proposed. The developed method makes possible to obtain recognition models having high generalizing properties, simplicity and interpretation, and also to reduce the time for model building. The results of experiments allow recommending the proposed method for use in practice.
A Systematic Review of the Burden of Multidrug-Resistant Healthcare-Associated Infections Among Intensive Care Unit Patients in Southeast Asia: The Rise of Multidrug-Resistant Acinetobacter baumannii

OBJECTIVE To summarize the clinical burden (cumulative incidence, prevalence, case fatality rate and length of stay) and economic burden (healthcare cost) of healthcare-associated infections (HAIs) due to multidrug-resistant organisms (MDROs) among patients in intensive care units (ICUs) in Southeast Asia. DESIGN Systematic review. METHODS We conducted a comprehensive literature search in PubMed, EMBASE, CINAHL, EconLit, and the Cochrane Library databases from their inception through September 30, 2016. Clinical and economic burdens and study quality were assessed for each included study. RESULTS In total, 41 studies met our inclusion criteria; together, 22,876 ICU patients from 7 Southeast Asian countries were included. The cumulative incidence of HAI caused by A. baumannii (AB) in Southeast Asia is substantially higher than has been reported in other regions, especially carbapenem-resistant AB (CRAB; 64.91%) and multidrug-resistant AB (MDR-AB) (58.51%). Evidence of a dose–response relationship between different degrees of drug resistance and excess mortality due to AB infections was observed. Adjusted odds ratios were 1.23 (95% confidence interval [CI], 0.51–3.00) for MDR-AB, 1.72 (95% CI, 0.77–3.80) for extensively drug-resistant AB (XDR-AB), and 1.82 (95% CI, 0.55–6.00) for pandrug-resistant AB (PDR-AB). There is, however, a paucity of published data on additional length of stay and costs attributable to MDROs. CONCLUSIONS This review highlights the challenges in addressing MDROs in Southeast Asia, where HAIs caused by MDR gram-negative bacteria are abundant and have a strong impact on society. With our findings, we hope to draw the attention of clinicians and policy makers to the problem of antibiotic resistance and to issue a call for action in the management of MDROs. Infect Control Hosp Epidemiol 2018;39:525–533
Repeat-mediated deletions can be induced by a chromosomal break far from a repeat, but multiple pathways suppress such rearrangements

Here, Mendez-Dorantes et al. investigated how far a chromosomal double-strand break (DSB) can be positioned from a repeat sequence to induce repeat-mediated rearrangements in mammalian cells. Using a novel reporter assay in mouse embryonic stem cells, they found that a DSB separated from the 3′ repeat by 28.4 kb can still substantially induce RMDs, indicating that a DSB is sufficient to induce RMDs at a relatively far distance.
Connecting Opinions to Opinion-Leaders: A Case Study on Brazilian Political Protests

Social media applications have assumed an important role in decision-making process of users, affecting their choices about products and services. In this context, understanding and modeling opinions, as well as opinion-leaders, have implications for several tasks, such as recommendation, advertising, brand evaluation etc. Despite the intrinsic relation between opinions and opinion-leaders, most recent works focus exclusively on either understanding the opinions, by Sentiment Analysis (SA) proposals, or identifying opinion-leaders using Influential Users Detection (IUD). This paper presents a preliminary evaluation about a combined analysis of SA and IUD. In this sense, we propose a methodology to quantify factors in real domains that may affect such analysis, as well as the potential benefits of combining SA Methods with IUD ones. Empirical assessments on a sample of tweets about the Brazilian president reveal that the collective opinion and the set of top opinion-leaders over time are inter-related. Further, we were able to identify distinct characteristics of opinion propagation, and that the collective opinion may be accurately estimated by using a few top-k opinion-leaders. These results point out the combined analysis of SA and IUD as a promising research direction to be further exploited.
Improving condition- and environment-invariant place recognition with semantic place categorization

The place recognition problem comprises two distinct subproblems; recognizing a specific location in the world (“specific” or “ordinary” place recognition) and recognizing the type of place (place categorization). Both are important competencies for mobile robots and have each received significant attention in the robotics and computer vision community, but usually as separate areas of investigation. In this paper, we leverage the powerful complementary nature of place recognition and place categorization processes to create a new hybrid place recognition system that uses place context to inform place recognition. We show that semantic place categorization creates an informative natural segmenting of physical space that in turn enables significantly better place recognition performance in comparison to existing techniques. In particular, this new semantically-informed approach adds robustness to significant local changes within the environment, such as transitioning between indoor and outdoor environments or between dark and light rooms in a house, complementing the capabilities of current condition-invariant techniques that are robust to globally consistent change (such as day to night cycles). We perform experiments using 4 novel benchmark datasets and show that semantically-informed place recognition outperforms the previous state-of-the-art systems. Like it does for object recognition [1], we believe that semantics can play a key role in boosting conventional place recognition and navigation performance for robotic systems.
Satellite Communications Systems

ABSTRACT OF THE DISCLOSURE Bursts transmitted from different ground stations are combined, in time-staggered fashion to form a block, at a satellite and are retransmitted therefrom. A ground station transmits an initial access signal and monitors the position of this signal in a received block to adjust the theoretical phase of a burst to be transmitted. Access time is reduced by adjusting the phase first to a delayed intermediate theoretical phase and then converting it to the theoretical phase proper under programme control.
Evaluation of Land Surface Models in Reproducing Satellite Derived Leaf Area Index over the High-Latitude Northern Hemisphere. Part II: Earth System Models

Leaf Area Index (LAI) is a key parameter in the Earth System Models (ESMs) since it strongly affects land-surface boundary conditions and the exchange of matter and energy with the atmosphere. Observations and data products derived from satellite remote sensing are important for the validation and evaluation of ESMs from regional to global scales. Several decades’ worth of satellite data products are now available at global scale which represents a unique opportunity to contrast observations against model results. The objective of this study is to assess whether ESMs correctly reproduce the spatial variability of LAI when compared with satellite data and to compare the length of the growing season in the different models with the satellite data. To achieve this goal we analyse outputs from 11 coupled carbon-climate models that are based on the set of new global model simulations planned in support of the IPCC Fifth Assessment Report. We focus on the average LAI and the length of the growing season on Northern Hemisphere over the period 1986–2005. Additionally we compare the results with previous analyses (Part I) of uncoupled land surface models (LSMs) to assess the relative contribution of vegetation and climatic drivers on the correct representation of LAI. Our results show that models tend to overestimate the average values of LAI and have a longer growing season due to the later dormancy. The similarities with the uncoupled models suggest that representing the correct vegetation fraction with the associated parameterizations; is more important in controlling the distribution and value of LAI than the climatic variables.
A primary insight into the molecular phylogeny of Colias FABRICIUS, 1807 (Pieridae, Coliadinae) complex of South America.

The data on molecular phylogeny of the Colias complex of South America (SA), obtained via barcoding a mitochondrial part of genome, are reported. Barcoding was trialed employing the Barcoding of Life Database platform and comprised 93 specimens of SA Colias sp. plus 2 outgroup specimens (C. philodice guatemalena from North America). It is established that Colias sp. from SA form a single monophyletic clade, characterized by notable interspecific mutational divergences (3.5-4.5%) and moderate intraspecific ones (0.3-0.9%). It also reveals the occurrence of 3 well-established (notably diverged genetically) species (C. dimera, C. vauthierii, and C. alticola, the latter re-raised to sp. level), plus a complex of 3 'emerging' species (C. lesbia, C. euxanthe, and C. flaveola) which are weakly differentiated genetically. Furthermore, it disregards the sp. status of taxa weberbaueri, mossi, nigerrima, erika, blameyi, and mendozina, as certain evidences are being brought to consider them ssp. of a clinal type of super-sp. C. flaveola s. lat. Importantly, the clade formed by SA Colias is found to be sister to the one comprising Colias sp. occurring outside the region (in Eurasia, North America, and Africa). A direct comparison of the results obtained for SA Colias with those for worldwide Colias (GenBank data) leads to the conclusion that these are largely divergent autochtonous subcomplexes, being in fact subgenera s. lat. of genus Colias. The first subgenus comprising all SA Colias sp. and named Aucolias (Austral Colias, or of southern hemisphere stem) is sister to the second one (comprising all Colias sp. from the Old and New Worlds), for which the name Colias (Colias) s. str. is preserved.
Basics of using connected me system in the transmission of information signals

It has been established that the transfer of data through the human body is a very real task, which was confirmed by the results of modeling. Ericsson's (namely Telefonaktiebolaget L. M. Ericsson) numerous laboratory studies have shown the safety of Connected Me technology for the human body. As a confirmation of this, the estimated SAR level for the main operating frequencies of the system was manually and using the "FDTDpro" program, and in all cases the values were much lower than the set threshold level of 2 W / kg. Also, the safety value is the magnitude of the maximum current Imax_Tx of 11 mA, which is 9 mA below the limit set for contact currents (20 mA). Due to the fact that modern electronic gadgets can not be imagined without a touch screen, Connected Me technology is a natural hardware complement of the functions of various mobile telecommunication devices of special purpose.
Epidemic spreading and immunization strategy in multiplex networks

A more connected world has brought major consequences such as facilitate the spread of diseases all over the world to quickly become epidemics, reason why researchers are concentrated in modeling the propagation of epidemics and outbreaks in multilayer networks. In this networks all nodes interact in different layers with different type of links. However, in many scenarios such as in the society, a multiplex network framework is not completely suitable since not all individuals participate in all layers. In this paper, we use a partially overlapped, multiplex network where only a fraction of the individuals are shared by the layers. We develop a mitigation strategy for stopping a disease propagation, considering the Susceptible-Infected- Recover model, in a system consisted by two layers. We consider a random immunization in one of the layers and study the effect of the overlapping fraction in both, the propagation of the disease and the immunization strategy. Using branching theory, we study this scenario theoretically and via simulations and find a lower epidemic threshold than in the case without strategy.
The NEIL1 G83D germline DNA glycosylase variant induces genomic instability and cellular transformation

Base excision repair (BER) is a key genome maintenance pathway. The NEIL1 DNA glycosylase recognizes oxidized bases, and likely removes damage in advance of the replication fork. The rs5745906 SNP of the NEIL1 gene is a rare human germline variant that encodes the NEIL1 G83D protein, which is devoid of DNA glycosylase activity. Here we show that expression of G83D NEIL1 in MCF10A immortalized but non-transformed mammary epithelial cells leads to replication fork stress. Upon treatment with hydrogen peroxide, we observe increased levels of stalled replication forks in cells expressing G83D NEIL1 versus cells expressing the wild-type (WT) protein. Double-strand breaks (DSBs) arise in G83D-expressing cells during the S and G2/M phases of the cell cycle. Interestingly, these breaks result in genomic instability in the form of high levels of chromosomal aberrations and micronuclei. Cells expressing G83D also grow in an anchorage independent manner, suggesting that the genomic instability results in a carcinogenic phenotype. Our results are consistent with the idea that an inability to remove oxidative damage in an efficient manner at the replication fork leads to genomic instability and mutagenesis. We suggest that individuals who harbor the G83D NEIL1 variant face an increased risk for human cancer.
Investigation of self-adaptive differential evolution on the CEC-2013 real-parameter single-objective optimization testbed

Self-adaptive differential evolution (SaDE) is a wellknown DE variant, which has received considerable attention since it was developed. SaDE gradually adapts its trial vector generation strategy and the accompanying parameter setting via learning the preceding performance of multiple candidate strategies and their associated parameter settings. This work systematically investigates SaDE on the CEC-2013 real-parameter single-objective optimization testbed. Parameter sensitivity analysis is carried out by using advanced statistical hypothesis testing methods, aiming to detect statistically significantly superior parameter settings. This analysis reveals that SaDE is actually less sensitive to the parameter choice since quite a number of parameter settings can lead to the statistically significantly better performance than the other settings. Based on this finding, we report SaDE's performance using one of the parameter settings advocated by sensitivity analysis and statistically compare this performance with that of a widely used classic DE (DE/rand/1/bin). The comparison results significantly favor SaDE.
Effects of a 6-month caloric restriction induced-weight loss program in obese postmenopausal women with and without the metabolic syndrome: a MONET study

Objective: To compare the effects of a caloric restriction (CR) on body composition, lipid profile, and glucose homeostasis in obese postmenopausal women with and without metabolic syndrome (MetS). Methods: Secondary analyses were performed on 73 inactive obese postmenopausal women (age 57.7 ± 4.8 years; body mass index 32.4 ± 4.6 kg/m2) who participated in the 6-month CR arm of a study of the Montreal-Ottawa New Emerging Team. The harmonized MetS definition was used to categorize participants with MetS (n = 20, 27.39%) and without MetS (n = 53, 72.61%). Variables of interest were: body composition (dual-energy X-ray absorptiometry), body fat distribution (computed tomography scan), glucose homeostasis at fasting state and during a euglycemic/hyperinsulinemic clamp, fasting lipids, and resting blood pressure. Results: By design, the MetS group had a worse cardiometabolic profile, whereas both groups were comparable for age. Fifty-five participants out of 73 displayed no change in MetS status after the intervention. Twelve participants out of 20 (or 60.0%) in the MetS group had no more MetS after weight loss (P = NS), whereas 6 participants out of 53 (or 11.3%) in the other group developed the MetS after the intervention (P = NS). Overall, indices of body composition and body fat distribution improved significantly and similarly in both groups (P between 0.03 and 0.0001). Furthermore, with the exception of triglyceride levels and triglycerides/high-density lipoprotein cholesterol ratio, which decrease significantly more in the MetS group (P ⩽ 0.05), no difference was observed between groups for the other variables of the cardiometabolic profile. Conclusions: Despite no overall significant effects on MetS, heteregeneous results were obtained in response to weight loss in the present study, with some improving the MetS, whereas other displaying deteriorations. Further studies are needed to identify factors and phenotypes associated with positive and negative cardiometabolic responses to CR intervention.
Analysis of long-range interactions in primary human cells identifies cooperative CFTR regulatory elements

A mechanism by which control DNA elements regulate transcription over large linear genomic distances is by achieving close physical proximity with genes, and looping of the intervening chromatin paths. Alterations of such regulatory ‘chromatin looping’ systems are likely to play a critical role in human genetic disease at large. Here, we studied the spatial organization of a ≈790 kb locus encompassing the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Dysregulation of CFTR is responsible for cystic fibrosis, which is the most common lethal genetic disorder in Caucasian populations. CFTR is a relatively large gene of 189 kb with a rather complex tissue-specific and temporal expression profile. We used chromatin conformation at the CFTR locus to identify new DNA sequences that regulate its transcription. By comparing 5C chromatin interaction maps of the CFTR locus in expressing and non-expressing human primary cells, we identified several new contact points between the CFTR promoter and its surroundings, in addition to regions featuring previously described regulatory elements. We demonstrate that two of these novel interacting regions cooperatively increase CFTR expression, and suggest that the new enhancer elements located on either side of the gene are brought together through chromatin looping via CTCF.
Third Party Tracking in the Mobile Ecosystem

Third party tracking allows companies to identify users and track their behaviour across multiple digital services. This paper presents an empirical study of the prevalence of third-party trackers on 959,000 apps from the US and UK Google Play stores. We find that most apps contain third party tracking, and the distribution of trackers is long-tailed with several highly dominant trackers accounting for a large portion of the coverage. The extent of tracking also differs between categories of apps; in particular, news apps and apps targeted at children appear to be amongst the worst in terms of the number of third party trackers associated with them. Third party tracking is also revealed to be a highly trans-national phenomenon, with many trackers operating in jurisdictions outside the EU. Based on these findings, we draw out some significant legal compliance challenges facing the tracking industry.
From Myeloma Precursor Disease to Multiple Myeloma: New Diagnostic Concepts and Opportunities for Early Intervention

Since monoclonal gammopathy of undetermined significance (MGUS) was first described more than 30 years ago, the definition of the entity has evolved. Today, 3 distinct clinical MGUS subtypes have been defined: non–immunoglobulin M (IgM; IgG or IgA) MGUS, IgM MGUS, and light chain MGUS. Each clinical MGUS subtype is characterized by unique intermediate stages and progression events. Although we now have strong evidence that multiple myeloma is consistently preceded by a precursor state at the molecular level, there is urgent need to better understand mechanisms that regulate transformation from precursor to full-blown multiple myeloma. In the future, if such knowledge was available, it would allow clinicians to define high-risk and low-risk precursor patients for a more tailored clinical management. Also, it would provide insights on the individual patient's disease biology, which, in turn, can be used for targeted and more individualized treatment strategies. On the basis of current clinical guidelines, patients diagnosed with MGUS and smoldering myeloma should not be treated outside of clinical trials. In the near future, it seems reasonable to believe that high-risk precursor patients will likely become candidates for early treatment strategies. In this review, we discuss novel insights from recent studies and propose future directions of relevance for clinical management and research studies. Clin Cancer Res; 17(6); 1243–52. ©2011 AACR.