Miracle-dz/UniFAR-FTUs huggingface dataset:
Signature-Tagged Mutagenesis in a Chicken Infection Model Leads to the Identification of a Novel Avian Pathogenic Escherichia coli Fimbrial Adhesin

The extraintestinal pathogen, avian pathogenic E. coli (APEC), known to cause systemic infections in chickens, is responsible for large economic losses in the poultry industry worldwide. In order to identify genes involved in the early essential stages of pathogenesis, namely adhesion and colonization, Signature-tagged mutagenesis (STM) was applied to a previously established lung colonization model of infection by generating and screening a total of 1,800 mutants of an APEC strain IMT5155 (O2:K1:H5; Sequence type complex 95). The study led to the identification of new genes of interest, including two adhesins, one of which coded for a novel APEC fimbrial adhesin (Yqi) not described for its role in APEC pathogenesis to date. Its gene product has been temporarily designated ExPEC Adhesin I (EA/I) until the adhesin-specific receptor is identified. Deletion of the ExPEC adhesin I gene resulted in reduced colonization ability by APEC strain IMT5155 both in vitro and in vivo. Furthermore, complementation of the adhesin gene restored its ability to colonize epithelial cells in vitro. The ExPEC adhesin I protein was successfully expressed in vitro. Electron microscopy of an afimbriate strain E. coli AAEC189 over-expressed with the putative EA/I gene cluster revealed short fimbrial-like appendages protruding out of the bacterial outer membrane. We observed that this adhesin coding gene yqi is prevalent among extraintestinal pathogenic E. coli (ExPEC) isolates, including APEC (54.4%), uropathogenic E. coli (UPEC) (65.9%) and newborn meningitic E. coli (NMEC) (60.0%), and absent in all of the 153 intestinal pathogenic E. coli strains tested, thereby validating the designation of the adhesin as ExPEC Adhesin I. In addition, prevalence of EA/I was most frequently associated with the B2 group of the EcoR classification and ST95 complex of the multi locus sequence typing (MLST) scheme, with evidence of a positive selection within this highly pathogenic complex. This is the first report of the newly identified and functionally characterized ExPEC adhesin I and its significant role during APEC infection in chickens.
Changes in Crystallinity of the HDPE Matrix in Composites with Cellulosic Fiber Using DSC and FTIR

The ageing of HDPE/cellulosic fiber composite exposed to drastic weather and the percentages of cellulosic fibers are responsible for some changes in the crystallinity of component matrix (HDPE). Two types of samples have been evaluated during different periods of time (up to 90 days). One in which cellulosic fibers have not been treated and another in which fibers have been given a treatment with a coupling agent, silane type, which favours the fiber adhesion to the matrix. Two instrumental analysis techniques have been used to determine the crystallinity changes of HDPE: Fourier Transform Infrared spectrophotometry (FTIR) and Differential Scanning Calorimetry (DSC).
Mechanical and Anticorrosive Properties of Graphene/Epoxy Resin Composites Coating Prepared by in-Situ Method

The graphene nanosheets-based epoxy resin coating (0, 0.1, 0.4 and 0.7 wt %) was prepared by a situ-synthesis method. The effect of polyvinylpyrrolidone/reduced graphene oxide (PVP-rGO) on mechanical and thermal properties of epoxy resin coating was investigated using nanoindentation technique and thermogravimetric analysis, respectively. A significant enhancement (ca. 213% and 73 °C) in the Young modulus and thermal stability of epoxy resin coating was obtained at a loading of 0.7 wt %, respectively. Furthermore, the erosion resistance of graphene nanosheets-based epoxy resin coating was investigated by electrochemical measurement. The results showed also that the Rrcco (ca. 0.3 mm/year) of graphene nanosheets-based epoxy resin coating was far lower than neat epoxy resin (1.3 mm/year). Thus, this approach provides a novel route for improving erosion resistance and mechanical-thermal stability of polymers coating, which is expected to be used in mechanical-thermal-corrosion coupling environments.
Event-driven support of real-time sentient objects

The emergence of applications operating independently of direct human control is inevitable. Research on high-level models for this class of applications - e.g. on autonomous agents and distributed AI - has revealed the shortcomings of current architectures and middleware interaction paradigms. If we focus on complex real-time systems made of embedded components, that evidence is even more striking. Event models have shown to be quite promising in this arena, but they often lack one or several of the following key points: seamless integration with a programming model; adequate layer structure; and the provision of support for nonfunctional attributes, such as timeliness or quality of service, or security. This paper discusses infrastructure support to construct large-scale proactive applications based on the use of real-time sentient objects, and is especially devoted to the latter two points.
Contrasting the Spread of Misinformation in Online Social Networks

Online social networks are nowadays one of the most effective and widespread tools used to share information. In addition to being employed by individuals for communicating with friends and acquaintances, and by brands for marketing and customer service purposes, they constitute a primary source of daily news for a significant number of users. Unfortunately, besides legit news, social networks also allow to effectively spread inaccurate or even entirely fabricated ones. Also due to sensationalist claims, misinformation can spread from the original sources to a large number of users in a very short time, with negative consequences that, in extreme cases, can even put at risk public safety or health. In this work we discuss and propose methods to limit the spread of misinformation over online social networks. The issue is split in two separate sub-problems. We first aim to identify the most probable sources of the misinformation among the subset of users that have been reached by it. In the second step, assuming to know the misinformation sources, we want to locate a minimum number of monitors (that is, entities able to identify and block false information) in the network in order to prevent that the misinformation campaign reaches some “critical” nodes while maintaining low the number of nodes exposed to the infection. For each of the two issues, we provide both heuristics and mixed integer programming formulations. To verify the quality and efficiency of our suggested solutions, we conduct experiments on several real-world networks. The results of this extensive experimental phase validate our heuristics as effective tools to contrast the spread of misinformation in online social networks. Regarding the source identification step, our approach showed success rates above 80% in most of the considered settings, and above 60% in almost all of them. With respect to the second issue, our heuristic proved to be able to obtain solutions that exceeded (in terms of number of required monitors) the ones obtained through our MILP-based approach of more than 20% in only few test scenarios. Our heuristics for both problems also proved to outperform significantly some previously proposed algorithms.
Maternal morbidity and mortality from severe sepsis: a national cohort study

Objectives To describe the incidence, characteristics and risk factors for critical care admission with severe maternal sepsis in the UK. Design National cohort study. Setting 198 critical care units in the UK. Participants 646 pregnant and recently pregnant women who had severe sepsis within the first 24 hours of admission in 2008–2010. Primary and secondary outcome measures Septic shock, mortality. Results Of all maternal critical care admissions, 14.4% (n=646) had severe sepsis; 10.6% (n=474) had septic shock. The absolute risk of maternal critical care admission with severe sepsis was 4.1/10 000 maternities. Pneumonia/respiratory infection (irrespective of the H1N1 pandemic influenza strain) and genital tract infection were the most common sources of sepsis (40% and 24%, respectively). We identified a significant gradient in the risk of severe maternal sepsis associated with increasing deprivation (RR=6.5; 95% CI 4.9 to 8.5 most deprived compared with most affluent women). The absolute risk of mortality was 1.8/100 000 maternities. The most common source of infection among women who died was pneumonia/respiratory infection (41%). Known risk factors for morbidity supported by this study were: younger age, multiple gestation birth and caesarean section. Significant risk factors for mortality in unadjusted analysis were: age ≥35 years (unadjusted OR (uOR)=3.5; 95% CI 1.1 to 10.6), ≥3 organ system dysfunctions (uOR=12.7; 95% CI 2.9 to 55.1), respiratory dysfunction (uOR=6.5; 95% CI1.9 to 21.6), renal dysfunction (uOR=5.6; 95% CI 2.3 to 13.4) and haematological dysfunction (uOR=6.5; 95% CI 2.9 to 14.6). Conclusions This study suggests a need to improve timely recognition of severe respiratory tract and genital tract infection in the obstetric population. The social gradient associated with the risk of severe sepsis morbidity and mortality raises important questions regarding maternal health service provision and usage.
Material Models for Hookean Materials with Voids or Cracks

Stress-strain relations for Hookean materials with spherical voids or penny-shaped microcracks are derived. The constitutive relation for voided material is based on the analytical expression by Eshelby whereas the theoretical work by Kachanov provided the foundation for the material model of microcracked material. The postulate of strain equivalence was shown to be incompatible with the analytical expression by Eshelby.
Prognostic value of tumor-infiltrating lymphocytes differs depending on histological type and smoking habit in completely resected non-small-cell lung cancer.

BACKGROUND T-cell infiltration in tumors has been used as a prognostic tool in non-small-cell lung cancer (NSCLC). However, the influence of smoking habit and histological type on tumor-infiltrating lymphocytes (TILs) in NSCLC remains unclear. PATIENTS AND METHODS We evaluated the prognostic significance of TILs (CD4+, CD8+, CD20+, and FOXP3+) according to histological type and smoking habit using automatic immunohistochemical staining and cell counting in 218 patients with NSCLC. RESULTS In multivariate survival analyses of clinical, pathological, and immunological factors, a high ratio of FOXP3+ to CD4+ T cells (FOXP3/CD4) [hazard ratio (HR): 4.46, P < 0.01 for overall survival (OS); HR: 1.96, P < 0.05 for recurrence-free survival (RFS)] and a low accumulation of CD20+ B cells (HR: 2.45, P = 0.09 for OS; HR: 2.86, P < 0.01 for RFS) were identified as worse prognostic factors in patients with adenocarcinoma (AD). In non-AD, a low number of CD8+ T cells were correlated with an unfavorable outcome (HR: 7.69, P < 0.01 for OS; HR: 3.57, P < 0.02 for RFS). Regarding smoking habit in AD, a high FOXP3/CD4 ratio was poorly prognostic with a smoking history (HR: 5.21, P < 0.01 for OS; HR: 2.38, P < 0.03 for RFS), whereas a low accumulation of CD20+ B cells (HR: 4.54, P = 0.03 for OS; HR: 2.94, P < 0.01 for RFS) was confirmed as an unfavorable factor in non-smokers with AD. CONCLUSIONS A low number of CD8+ T cells in non-AD, a high FOXP3/CD4 ratio in smokers with AD, and a low number of CD20+ B cells in non-smokers with AD were identified as independent unfavorable prognostic factors in resected NSCLC. Evaluating the influence of histological type and smoking habit on the immunological environment may lead to the establishment of immunological diagnosis and appropriate individualized immunotherapy for NSCLC.
Facing Your Opponents: Social Identification and Information Feedback in Contests

We experimentally investigate the effect of social identification and information feedback on individual behavior in contests. Identifying subjects through photo display decreases efforts. Providing information feedback about others’ effort does not affect the aggregate effort levels but it does change the dynamics of individual behavior. We develop a behavioral model based on relative payoff maximization, and use it to estimate the degree of pro-social/status-seeking behavior. We find that decrease in ‘social distance’ between group members through photo display promotes pro-social behavior. Information feedback reduces the within-group volatility in effort level and facilitates greater adherence to the ‘group norm. ’ Finally, in contrast to standard theoretical predictions, we find significant over-expenditure of efforts in all treatments. This overdissipation can be explained by a combination of non-monetary utility of winning and relative payoff maximization.
Dynamic dispersive spectrometer using a fiber Bragg grating for high pressure measurements

A new high resolution dispersive spectrometer has been developed to measure high pressure shock profiles every 10 ns using long Fiber Bragg Gratings. The performances are compared with a dynamic AWG-based spectrometer. Two small diameter fibers allow inserting in parallel two 50-mm long gratings into the target. The use of slightly chirped gratings provides the localization of the shock-wave along them. Placed along the target axis, a gratings reflected spectrum is “blue shifted”. The FBG's central wavelength are 1605 nm to cover a pressure range of 0–8 GPa. The new spectrometer is based on a femtosecond laser source, a long dispersive fiber and a fast acquisition system with an electrical bandwidth above 30 GHz. The experimental setup was a symmetric impact with 6061T6 aluminum, performed with a 110-mm in diameter single-stage gas gun. An impact velocity of 314 m/s is obtained and generated a sustained level of 2.1 GPa during few microseconds. A resulted Bragg shift of (16 ± 1) nm is measured. The dispersive spectrometer offers much greater resolution than the AWG one which is favorable to retrieve more easily a pressure profile.
Neural networks and neurofeedback in Parkinson's Disease

Aberrant neural network synchrony in basal ganglia thalamocortical circuits has been implicated in the pathophysiology of Parkinson’s disease. Manipulating these abnormal activation patterns may therefore offer a novel avenue for treating this disabling condition. Evidence suggests that network activity can be normalized with both dopaminergic drug treatment and deep brain stimulation (DBS), and protocols that directly target specific oscillatory patterns (―closed-loop DBS‖) are under development. Another potential avenue for the modulation of specific neural activation patterns is neurofeedback. This noninvasive technique entails providing a continuous update of one’s neural activity so that volitional control of selected brain regions, networks, or rhythms can be learned. This could be accompanied by specific therapeutic changes in behavior and clinical symptomatology in disease, according to the neural circuits that are modulated. Most neurofeedback research has used electroencephalography (EEG) but recently neurovascular signals measured with functional magnetic resonance imaging (fMRI) have been targeted as well. In this paper, we discuss the evidence implicating certain rhythms, particularly the beta (10–35 Hz) oscillation, in Parkinson’s disease. We also perform a systematic review evaluating the therapeutic efficacy of neurofeedback in Parkinson’s disease and make suggestions for future research.
The nature and effect of communication difficulties arising from interactions between district nurses and South Asian patients and their carers.

AIM The overall aim of the study was to examine how policy directives concerning the provision of individualized care were modified in their transformation into practice and the implications this carried for the care provided to patients from different ethnic backgrounds. This paper is concerned with one aspect, namely, examining the nature and effects of communication difficulties between the nurses and South Asian patients and their carers. METHODS An ethnographic approach was used. The study was undertaken in an English community National Health Service (NHS) Trust serving an ethnically diverse population. It comprised two stages. First, an organizational profile of the trust was undertaken in order to analyse the local policy context. Data were collected by means of in-depth interviews with managers and a review of policy documentation and caseload profiles. Second, a participant observational study was undertaken focusing on six district nursing teams. Purposive sampling was used to identify four teams with high ethnic minority caseloads and two teams with predominantly white ethnic majority caseloads. Interview transcripts and fieldnotes were analysed by drawing upon the principles of dimensional analysis. FINDINGS Over half of South Asian patients had little or no understanding of spoken English with women and older people the least likely to speak English. The limited use of professional interpreters and the concomitant heavy reliance on family members to translate highlighted how ethnic minority patients and carers who were not fluent in English were disadvantaged. The observed language barriers suggested that the content of advice on matters such as compliance with treatment regimes might not be fully understood. Psychological support of patients and carers was severely restricted. Moreover, the fact that follow-up visits were on occasions made to patients for whom there was no one available to interpret constrained on-going assessment of patients' needs. CONCLUSIONS The findings raise concerns regarding the quality of care provided to patients and carers who are nonusers of English and provide evidence of inequalities in service provision. However, not speaking English should not be a barrier to appropriate and effective nursing care. District nurses need to appreciate their responsibility to provide equitable services irrespective of a patient's linguistic background and seek to overcome the disadvantage experienced by ethnic minority patients.
Active Learning for Coreference Resolution

We present an active learning method for coreference resolution that is novel in three respects. (i) It uses bootstrapped neighborhood pooling, which ensures a class-balanced pool even though gold labels are not available. (ii) It employs neighborhood selection, a selection strategy that ensures coverage of both positive and negative links for selected markables. (iii) It is based on a query-by-committee selection strategy in contrast to earlier uncertainty sampling work. Experiments show that this new method outperforms random sampling in terms of both annotation effort and peak performance.
Prognostic Significance of Melanoma Differentiation and Trans-Differentiation

Cutaneous malignant melanomas share a number of molecular attributes such as limitless replicative potential that define capabilities acquired by most malignancies. Accordingly, much effort has been focused on evaluating and validating protein markers related to these capabilities to function as melanoma prognostic markers. However, a few studies have also highlighted the prognostic value of markers that define melanocytic differentiation and the plasticity of melanoma cells to trans-differentiate along several other cellular pathways. Here, we provide a comprehensive review and evaluation of the prognostic significance of melanocyte-lineage markers such as MITF and melanogenic proteins, as well as markers of vascular epithelial and neuronal differentiation.
Fluidic Kernels: Cooperative Execution of OpenCL Programs on Multiple Heterogeneous Devices

Programming heterogeneous computing systems with Graphics Processing Units (GPU) and multi-core CPUs in them is complex and time-consuming. OpenCL has emerged as an attractive programming framework for heterogeneous systems. But utilizing multiple devices in OpenCL is a challenge because it requires the programmer to explicitly map data and computation to each device. The problem becomes even more complex if the same OpenCL kernel has to be executed synergistically using multiple devices, as the relative execution time of the kernel on different devices can vary significantly, making it difficult to determine the work partitioning across these devices a priori. Also, after each kernel execution, a coherent version of the data needs to be established. In this work, we present FluidiCL, an OpenCL runtime that takes a program written for a single device and uses both the CPU and the GPU to execute it. Since we consider a setup with devices having discrete address spaces, our solution ensures that execution of OpenCL work-groups on devices is adjusted by taking into account the overheads for data management. The data transfers and data merging needed to ensure coherence are handled transparently without requiring any effort from the programmer. FluidiCL also does not require prior training or profiling and is completely portable across different machines. Across a set of diverse benchmarks having multiple kernels, our runtime shows a geomean speedup of nearly 64% over a high-end GPU and 88% over a 4-core CPU. In all benchmarks, performance of our runtime comes to within 13% of the best of the two devices.
A flexible and modular crosslingual voice conversion system

A cross-lingual voice conversion system aims at modifying the timbral structure of recorded sentences from a source speaker, in order to obtain processed sentences which are perceived as the same sentences uttered by a target speaker. This work presents the cross-lingual voice conversion problem as a network of related sub-problems and discuss several techniques for solving each of these sub-problems, in the context of a modular implementation that facilitates comparisons between competing techniques. The implemented system aims at high-quality cross-lingual voice conversion in a text-independent setting, i.e. where the training sets of sentences recorded by source and target speakers are not the same. New strategies are introduced, such as artificial phonetic maps, N -likelihood clustering and normalized frequency warping, which are evaluated through numerical experiments.
How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?

A key hypothesis in sensory system neuroscience is that sensory representations are adapted to the statistical regularities in sensory signals and thereby incorporate knowledge about the outside world. Supporting this hypothesis, several probabilistic models of local natural image regularities have been proposed that reproduce neural response properties. Although many such physiological links have been made, these models have not been linked directly to visual sensitivity. Previous psychophysical studies of sensitivity to natural image regularities focus on global perception of large images, but much less is known about sensitivity to local natural image regularities. We present a new paradigm for controlled psychophysical studies of local natural image regularities and compare how well such models capture perceptually relevant image content. To produce stimuli with precise statistics, we start with a set of patches cut from natural images and alter their content to generate a matched set whose joint statistics are equally likely under a probabilistic natural image model. The task is forced choice to discriminate natural patches from model patches. The results show that human observers can learn to discriminate the higher-order regularities in natural images from those of model samples after very few exposures and that no current model is perfect for patches as small as 5 by 5 pixels or larger. Discrimination performance was accurately predicted by model likelihood, an information theoretic measure of model efficacy, indicating that the visual system possesses a surprisingly detailed knowledge of natural image higher-order correlations, much more so than current image models. We also perform three cue identification experiments to interpret how model features correspond to perceptually relevant image features.