Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinct Mutations Led to Inactivation of Type 1 Fimbriae Expression in Shigella spp.

Shigella spp. are responsible for bacillary dysentery in humans. The acquisition or the modification of the virulence plasmid encoding factors promoting entry of bacteria into and dissemination within epithelial cells was a critical step in the evolution of these bacteria from their Escherichia coli ancestor(s). Incorporation of genomic islands (GI) and gene inactivation also shaped interactions between these pathogens and their human host. Sequence analysis of the GI inserted next to the leuX tRNA gene in S. boydii, S. dysenteriae, S. flexneri, S. sonnei and enteroinvasive E. coli (EIEC) suggests that this region initially carried the fec, yjhATS and fim gene clusters. The fim cluster encoding type I fimbriae is systematically inactivated in both reference strains and clinical isolates and distinct mutations are responsible for this inactivation in at least three phylogenetic groups. To investigate consequences of the presence of fimbriae on the outcome of the interaction of Shigella with host cells, we used a S. flexneri strain harboring a plasmid encoding the E. coli fim operon. Production of fimbriae by this recombinant strain increased the ability of bacteria to adhere to and enter into epithelial cells and had no effect on their ability to disseminate from cell to cell. The observations that production of type I fimbriae increases invasion of epithelial cells and that independent mutations abolish fimbriae production in Shigella suggest that these mutations correspond to pathoadaptive events.
Association of Renal Stress/Damage and Filtration Biomarkers with Subsequent AKI during Hospitalization among Patients Presenting to the Emergency Department.

BACKGROUND AND OBJECTIVES Emergency departments (EDs) have a growing role in hospital admissions, but few studies address AKI biomarkers in the ED. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Patients admitted to the internal medicine service were enrolled during initial workup in the ED at Robert-Bosch-Hospital, Stuttgart, Germany. Daily serum creatinine (sCr) and urine output (UO) were recorded for AKI classification by Kidney Disease Improving Global Outcomes (KDIGO) criteria. Cystatin C, kidney injury molecule-1, liver-type fatty acid-binding protein, and neutrophil gelatinase-associated lipocalin were measured in blood and urine, and IL-18, insulin-like growth factor-binding protein 7 (IGFBP7), tissue inhibitor of metalloproteinases-2 (TIMP-2) and [TIMP-2]⋅[IGFBP7] were measured in urine collected at enrollment, after 6 hours, and the following morning. Association between these biomarkers and the end point of moderate-severe AKI (KDIGO stage 2-3) occurring within 12 hours of each sample collection was examined using generalized estimating equation logistic regression. Performance for prediction of the AKI end point using two previously validated [TIMP-2]-[IGFBP7] cutoffs was also tested. RESULTS Of 400 enrolled patients, 298 had sufficient sCr and UO data for classification by KDIGO AKI criteria: AKI stage 2 developed in 37 patients and AKI stage 3 in nine patients. All urinary biomarkers, sCr, and plasma cystatin C had statistically significant (P<0.05) odds ratios (ORs) for the AKI end point. In a multivariable model of the urine biomarkers and sCr, only [TIMP-2]⋅[IGFBP7] and sCr had statistically significant ORs. Compared with [TIMP-2]⋅[IGFBP7]<0.3 (ng/ml)(2)/1000, values between 0.3 and 2.0 (ng/ml)(2)/1000 indicated 2.5 (95% confidence interval [95% CI], 1.1 to 5.2) times the odds for the AKI end point and values >2.0 (ng/ml)(2)/1000 indicated 11.0 (95% CI, 4.4 to 26.9) times the odds. Addition of [TIMP-2]⋅[IGFBP7] to a clinical model significantly improved area under the receiver-operating characteristic curve from 0.67 (95% CI, 0.61 to 0.78) to 0.77 (95% CI, 0.72 to 0.86) (P<0.001); however, including both markers in the model was not significantly different from including either marker alone. CONCLUSIONS Urinary [TIMP-2]⋅[IGFBP7] with pre-established cutoffs provides valuable information about risk for imminent AKI in the ED that is complementary to sCr and clinical risk factors.
Individual Difference Effects on Performance in a Complex, Multi-Decision-Making Environment

The present research examines the impact of cognitive style and short-term memory (STM) capacity on the computer interface usability of a pilot simulation. Participants screened for individual differences in cognitive style and STM capacity were randomly assigned to a training condition within the Multi-Attribute Task Battery (MAT; Arnegard & Comstock, 1991). Training conditions varied in automation settings (adaptive versus static). Participants transferred to a novel static condition. Between subjects independent variables were individual differences in STM capacity (high, low), cognitive style (analytic, holistic, quasi-rational), and training (static versus adaptive). Within subjects independent variables were training (four blocks) and transfer (four blocks) sessions. Dependent variables were accuracy and reaction time. Results suggest that individual differences in STM capacity and cognitive style are orthogonal constructs that interact to affect skill acquisition and strategy development for visual-spatial tasks. Implications related to computer interface design are discussed.
Surface models of tube trees

This paper describes a new method for generating surfaces of branching tubular structures with given center-lines and radii. As the centerlines are not straight lines, the cross-sections are not parallel and well-known algorithms for surface tiling from parallel cross-sections cannot be used. Nonparallel cross-sections can be tiled by means of the maximal-disc interpolation method; special methods for branching-structures modeling by means of convolution surfaces produce excellent results, but these methods are more complex than our approach. The proposed method tiles nonparallel circular cross-sections and constructs a topologically-correct surface mesh. The method is not artifact-free, but it is fast and simple. The surface mesh serves as a data representation of a vessel tree suitable for real-time virtual reality operation planning and operation support within a medical application. Proposed method extracts a "classical" polygonal representation, which can be used in common surface-oriented graphic accelerators
A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.
Change of Brain Functional Connectivity in Patients With Spinal Cord Injury: Graph Theory Based Approach

Objective To investigate the global functional reorganization of the brain following spinal cord injury with graph theory based approach by creating whole brain functional connectivity networks from resting state-functional magnetic resonance imaging (rs-fMRI), characterizing the reorganization of these networks using graph theoretical metrics and to compare these metrics between patients with spinal cord injury (SCI) and age-matched controls. Methods Twenty patients with incomplete cervical SCI (14 males, 6 females; age, 55±14.1 years) and 20 healthy subjects (10 males, 10 females; age, 52.9±13.6 years) participated in this study. To analyze the characteristics of the whole brain network constructed with functional connectivity using rs-fMRI, graph theoretical measures were calculated including clustering coefficient, characteristic path length, global efficiency and small-worldness. Results Clustering coefficient, global efficiency and small-worldness did not show any difference between controls and SCIs in all density ranges. The normalized characteristic path length to random network was higher in SCI patients than in controls and reached statistical significance at 12%-13% of density (p<0.05, uncorrected). Conclusion The graph theoretical approach in brain functional connectivity might be helpful to reveal the information processing after SCI. These findings imply that patients with SCI can build on preserved competent brain control. Further analyses, such as topological rearrangement and hub region identification, will be needed for better understanding of neuroplasticity in patients with SCI.
Activation of p53 stimulates proteasome‐dependent truncation of eIF4E‐binding protein 1 (4E‐BP1)

Background information. The translational inhibitor protein 4E‐BP1 [eIF4E (eukaryotic initiation factor 4E)‐binding protein 1] regulates the availability of polypeptide chain initiation factor eIF4E for protein synthesis. Initiation factor eIF4E binds the 5′ cap structure present on all cellular mRNAs. Its ability to associate with initiation factors eIF4G and eIF4A, forming the eIF4F complex, brings the mRNA to the 43S complex during the initiation of translation. Binding of eIF4E to eIF4G is inhibited in a competitive manner by 4E‐BP1. Phosphorylation of 4E‐BP1 decreases the affinity of this protein for eIF4E, thus favouring the binding of eIF4G and enhancing translation. We have previously shown that induction or activation of the tumour suppressor protein p53 rapidly leads to 4E‐BP1 dephosphorylation, resulting in sequestration of eIF4E, decreased formation of the eIF4F complex and inhibition of protein synthesis.
What are they doing and how are they doing it? Rural student experiences in virtual schooling

This qualitative study examined a Canadian virtual school learning experience for students and the kinds of support and assistance most frequently used and valued by students learning in a virtual environment. Students were interviewed and observed during their virtual school classes. In-school teachers were also interviewed and online teachers were also observed. Data were analyzed using the constant comparative method. Findings indicated that during their scheduled asynchronous class time students were often assigned seatwork or provided time to work on assignments, however, students rarely used this time to complete virtual schoolwork. It was during their synchronous class time that both the students and the online teachers were most productive. Students sought assistance from local classmates before turning to online teacher or in-school teachers, and did not use the other support systems provided by the virtual school. Resume Cette etude qualitative a porte sur une experience canadienne d’apprentissage pour les eleves en ecole virtuelle ainsi que les types de soutien et d’aide les plus couramment utilises et prises par les etudiants qui font des apprentissages dans un environnement virtuel. Les etudiants ont ete interviewes et observes pendant leur cours virtuels. Des enseignants travaillant a l’ecole ont egalement ete interviewes et des enseignants travaillant en ligne ont aussi ete observes. Les donnees recueillies ont ete analysees a l’aide de la methode comparative constante. Les resultats demontrent que pendant leur temps de class asynchrone determine, les etudiants se faisaient souvent donner du travail individuel ou donner du temps pour travailler a leurs devoirs. Toutefois, les etudiants utilisaient rarement ce temps pour effectuer des travaux scolaires virtuels. C’etait durant leur temps de classe synchrone qu’a la fois les etudiants et les enseignants en ligne etaient les plus productifs. Les etudiants faisaient appel a l’aide de leurs pairs locaux avant de recourir a leur enseignant en ligne ou aux enseignants travaillant a l’ecole et ils n’utilisaient pas les autres systemes de soutien fournis par l’ecole virtuelle.
Distributed Beamforming using 1 Bit Feedback : from Concept to Realization

We present theoretical and experimental results for a distributed beamforming system based on a simple 1bit feedback algorithm. The algorithm is based on an iterative procedure, that synchronizes multiple transmitters to cooperatively send a common message signal coherently to a receiver, using only a single bit of feedback in each timeslot. Under this scheme, the transmitters make independent, random phase adjustments every timeslot, and retain only those phase adjustments that increase the SNR at the receiver. We describe the design of an experimental prototype to implement the beamforming algorithm, and present measurement data that shows the SNR gains from beamforming. We also analyze the convergence behavior of the procedure mathematically using a statistical approach. We show that the mathematical model gives accurate predictions for the convergence rate in static an d time-varying channels, and use the analysis to demonstrate the scalability of the algorithm.
Glial proteome changes in response to moderate hypothermia

Reactive glia plays a central role in neuroinflammation associated with secondary damage after brain injury. In order to understand the global effects of therapeutic hypothermia on glial activation and neuroinflammation, we performed proteomic profiling of glial cultures following inflammatory stimulation and hypothermic exposure. Primary mixed glial cultures prepared from mouse brains were stimulated with lipopolysaccharide and interferon‐γ under normothermic (37°C) or moderate hypothermic (29°C) conditions, and their proteome profiles were compared by LC‐ESI‐MS/MS. Differentially expressed proteins were determined by high‐throughput label‐free quantification. Under hypothermic conditions, 64 and 16 proteins were upregulated (≥1.5‐fold) and downregulated (≤ 0.7‐fold), respectively, compared to normothermic conditions. More importantly, hypothermia altered the abundance of 143 proteins that were either increased or decreased by inflammatory stimulation. The results were validated for several proteins (ICAM‐1, STAT‐1, YWHAB, and IFIT‐3) by Western blot analysis. Pathway and network analysis indicate that hypothermia influences various biological functions of glia such as molecular transport, cell movement, immune response, cell death, and stress response. In conclusion, moderate hypothermia seems to have a significant effect on the protein expression profiles of brain glia and possibly ensuing neuroinflammation. These proteins may be involved in the protective mechanism of hypothermia against brain injuries.
Innovation and Organization: Value and Competition in Selection Systems

New definitions are proposed for the concepts ‘innovation’ and ‘organization’ by looking at the concepts in terms of value and competition and using the framework of the selection system. Also, new definitions are proposed for ‘importance of an innovation’ and ‘stylistic innovation’. Some results can be directly derived from the definitions, such as that economic entities can exist that are organizations in the perception of the individual members and groups of competing actors in the perception of others. Together the new definitions provide a foundation for a better understanding of not just the concepts themselves but also of the relationships between the type and importance of innovations and the most likely characteristics of successful innovators.
Into the Blue: Better Caustics through Photon Relaxation

The photon mapping method is one of the most popular algorithms employed in computer graphics today. However, obtaining good results is dependent on several variables including kernel shape and bandwidth, as well as the properties of the initial photon distribution. While the photon density estimation problem has been the target of extensive research, most algorithms focus on new methods of optimising the kernel to minimise noise and bias. In this paper we break from convention and propose a new approach that directly redistributes the underlying photons. We show that by relaxing the initial distribution into one with a blue noise spectral signature we can dramatically reduce background noise, particularly in areas of uniform illumination. In addition, we propose an efficient heuristic to detect and preserve features and discontinuities. We then go on to demonstrate how reconfiguration also permits the use of very low bandwidth kernels, greatly improving render times whilst reducing bias.
A Deformable Smart Skin for Continuous Sensing Based on Electrical Impedance Tomography

In this paper, we present a low-cost, adaptable, and flexible pressure sensor that can be applied as a smart skin over both stiff and deformable media. The sensor can be easily adapted for use in applications related to the fields of robotics, rehabilitation, or costumer electronic devices. In order to remove most of the stiff components that block the flexibility of the sensor, we based the sensing capability on the use of a tomographic technique known as Electrical Impedance Tomography. The technique allows the internal structure of the domain under study to be inferred by reconstructing its conductivity map. By applying the technique to a material that changes its resistivity according to applied forces, it is possible to identify these changes and then localise the area where the force was applied. We tested the system when applied to flat and curved surfaces. For all configurations, we evaluate the artificial skin capabilities to detect forces applied over a single point, over multiple points, and changes in the underlying geometry. The results are all promising, and open the way for the application of such sensors in different robotic contexts where deformability is the key point.
Unsupervised Classification of Biomedical Abstracts Using Lexical Association

The task of text classification is the assignment of labels that describe texts' char- acteristics, such as topic, genre or sentiment. Supervised machine learning techniques such as Support Vector Machines or the simple but effective Na¨ ive Bayes have been successfully ap- plied to this task. However, it is not always practical to acquire a sufficient corpus of labelled examples to train these methods. For these cases we describe an unsupervised method for text classification based on two hypotheses. Firstly, we propose that the class of a document may be determined by calculating its constituent features' similarity with prototypical examples of each class. Secondly, we note the importance of class priors in NaBayes classifiers, and hypothesize that class distributions might be estimated using the relative frequency of prototype words. Performing experiments on a corpus of biomedical abstracts with topic information derived from the Medical Subject Headings (MeSH), we investigate the charac- teristics of the method when used in conjunction with basic, linguistic and knowledge-based features, and find that the performance of the unsupervised method is approximately 80% that of NaBayes. Our research is significant in that it highlights a candidate method with good potential for further improvement when training on unlabelled data.
On the role of frequency-based cues in the segmentation strategies of adult OV-VO bilinguals

The present investigation seeks to determine whether and under what circumstances can adult bilinguals deploy segmentation strategies characteristic of their two languages, or of their dominant language. To that end, we inquired whether the context language employed during the segmentation experiment (i.e., the language in which participants receive the instructions of the experiment) modulates the bilinguals' segmentation preferences given an ambiguous artificial language. Four groups of bilingual speakers of Basque (Object Verb, i.e., OV) and Spanish (Verb Object, i.e., VO) were sorted by their L1 and the context language (Basque or Spanish) in which the experiment was explained to the participants. We examined the bilinguals' segmentation preferences of an artificial language consistent of a strict alternation of frequent and infrequent syllables that allows two possible segmentations: a frequent-initial segmentation (i.e., in which frequent elements occur at initial position) and a frequent-final segmentation (i.e., in which frequent elements occur at final position). Results revealed that the context language modulated the segmentation preferences of L1Basque–L2Spanish bilinguals, but not the preferences of L1Spanish–L2Basque bilinguals. Adult bilinguals are thus able to deploy the frequency-based segmentation strategies of their two languages, though acquisition of the L2's strategy appears to be constrained.
An Efficient Transaction-Based GPU Implementation of Minimum Spanning Forest Algorithm

General Purpose GPUs (GPGPUs) are ideal platforms for parallel execution of applications with regular shared memory access patterns. However, majority of real world multithreaded applications require access to shared memory with irregular patterns. The Minimum Spanning Forest (MSF) calculation arises in many real world applications. The Boruvka's algorithm for calculating MSF has the most expressed parallelism; however, it is a challenging irregular algorithm to implement on GPUs. In this paper we show that a transaction- based design and implementation of the Boruvka's algorithm on GPU can handle some of the challenges arising due to irregularity. First, we identify the hotspots of the algorithm that are the main bottlenecks: edge discovery and merge. The edge discovery phase is implemented using lock-free synchronizations after extracting certain algebraic properties (e.g. monotonicity) of the computation. The merge phase, however, lacks such algebraic properties and hence we utilize a Software Transactional Memory (STM) based synchronization method. STM offers ease of use by guaranteeing deadlock/livelock-free behavior as opposed to blocking lock-based synchronization. It also increases programmability by providing high level abstractions for synchronization which facilitate a natural transition from algorithm design to implementation. In addition, we employ several optimization techniques in different phases of the algorithm to achieve load balance and enhanced GPU resource utilization. Experimental results show that our GPU-based implementation outperforms both the fastest sequential implementation and the existing STM-based implementation on multicore CPUs when tested on large-scale graphs with diverse densities.
Beyond member-checking: a dialogic approach to the research interview

This article presents a dialogic qualitative interview design for a narrative study of six international UK university students' motivation for learning English. Based on the work of Mikhail Bakhtin, this design was developed in order to address the limitations of member-checking [Lincoln, Y. S. , and E. G. Guba. 1985. Naturalistic Inquiry. Newbury Park, CA: Sage] as a means by which participants' responses to data and interpretation might be gathered. Through a personalized reflection on my design and consideration of attitudes to member-checking, I demonstrate that a more explicit co-constructedness is evident in both the design and the data generated, and I offer this design as a more collaborative, more ethical alternative to member-checking in particular, and as an approach to qualitative research interviews in general.