Miracle-dz/UniFAR-FTUs huggingface dataset:
One immunization strategy of complex networks

Aiming at improving respective shortcoming of target immunization and acquaintance immunization strategy, we present an immunization strategy which consists of two steps: choosing some node randomly and then adopting strengthened acquaintance immunization or improved target immunization according to different circumstances. This synthesis strategy retains the advantage of making decision based on pure local information, without needing information of global network structure or identification of the highest degree nodes. When the percentage of required vaccinations for immunity is the same as the targeted immunization, we get better results. Compare with other efficient strategies on a scale-free network model, the proposed strategy is significantly more effective and adaptive.
A Multiplex PCR based Method for the Identification of common Clinical Serotypes of Salmonella enterica subspecies enterica

A multiplex PCR method has been developed to differentiate between the most common clinical serotypes of Salmonella enterica subsp. enterica encountered in Washington State and the USA in general. Six genetic loci from S. Typhimurium and four from S. Typhi were used to create an assay consisting of two five-plex PCR reactions. The assays gave reproducible results with 30 different serotypes that represent the most common clinical isolates of S. enterica subsp. enterica. Of these, 22 serotypes gave unique amplification patterns when compared with each other and the other 8 serotypes were grouped into four pairs. These were further resolved by two additional PCR reactions. We compared the data from PCR serotyping with conventional serotyping and found that PCR serotyping was nearly as discriminatory as the conventional serotyping. The results from a blind test screening 111 clinical isolates revealed that 97% were correctly identified using the multiplex PCR assay. The assay can be easily performed on multiple samples with final results in less than 5 hours and, in conjunction with PFGE, forms a very robust test method for the molecular subtyping of Salmonella enterica serovar enterica. 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32
Cellular Analysis of Disorazole C1 and Structure–Activity Relationship of Analogs of the Natural Product

Structure–activity analyses of synthetic disorazole C1 and eight of its analogs indicate that the presence of a vinyl oxirane moiety or a tetraene sequence is not necessary for potent cytotoxic and antimitotic properties. Using an automated multiparameter fluorescence‐based cellular assay to simultaneously probe the effects of disorazole analogs on cellular microtubules, mitotic arrest, and cytotoxicity, we found that disorazole C1 enhanced the mitotic index and chromatin condensation and arrested cells in the G2/M phase of the cell cycle. All structural analogs and synthesis precursors of disorazole C1 were at least two orders of magnitude less potent than the parent compound, thus indicating that both the functional group array and the three‐dimensional conformation of the parent compound are critical for interaction with the biological target. We conclude that disorazole C1 is a potent inducer of mitotic arrest and hypothesize that this biological activity may be mediated by microtubule perturbation.
Kalman Filter Implementation With Improved Numerical Properties

This paper presents a new form of Kalman filter-the sigmaRho filter-useful for operational implementation in applications where stability and throughput requirements stress traditional implementations. The new mechanization has the benefits of square root filters in both promoting stability and reducing dynamic range of propagated terms. State standard deviations and correlation coefficients are propagated rather than covariance square root elements and these physically meaningful statistics are used to adapt the filtering for further ensuring reliable performance. Finally, all propagated variables can be scaled to predictable dynamic range so that fixed point procedures can be implemented for embedded applications. A sample problem from communications signal processing is presented that includes nonlinear state dynamics, extreme time-variation, and extreme range of system eigenvalues. The sigmaRho implementation is successfully applied at sample rates approaching 100 MHz to decode binary digital data from a 1.5-GHz carrier.
Phase-Interpolated Averaging for Analyzing Electroencephalography and Magnetoencephalography Epochs

Stimulus-locked averages of electroencephalography (EEG) and magnetoencephalography (MEG) epochs reveal characteristic waveforms. EEG/MEG generation models to have reconstruct such waveforms have been recently proposed. These models assume that evoked, phase-modulated, and amplitude-modulated activities occur solely or simultaneously. We propose a two-stage stimulus-locked averaging method, called phase-interpolated averaging, to investigate the EEG/MEG generation process. First, virtual EEG/MEG epochs, which would be obtained as if instantaneous phases for each time sampling point were on a phase-grid, are interpolated from actually measured EEG/MEG epochs. Then, the virtual EEG/MEG epochs are discrete Fourier transformed. A simulation revealed that the zeroth Fourier term revealed the evoked activity, the first Fourier term revealed the amplitude-modulated activity, and the condition number of the interpolation reflected the phase-modulated activity. On the basis of these facts, a preliminary EEG analysis implied that the evoked activity is much smaller than what would be expected by using conventional averaging, the evoked and phase-modulated activities simultaneously occur, and the amplitude-modulated activity occasionally associates with the evoked and phase-modulated activities. To the best of our knowledge, this is the first time that these three activities have been shown to coexist by actually separating them.
Integration of diagnosis and treatment of sleeping sickness in primary healthcare facilities in the Democratic Republic of the Congo

Control of human African trypanosomiasis (HAT) in the Democratic Republic of Congo (DRC) has always been a vertical programme, although attempts at integration in general health services were made in recent years. Now that HAT prevalence is declining, the integration question becomes even more crucial. We studied the level of attainment of integration of HAT case detection and management in primary care centres in two high‐prevalence districts in the province of Bandundu, DRC.
Lauric Acid Is an Inhibitor of Clostridium difficile Growth in Vitro and Reduces Inflammation in a Mouse Infection Model

Clostridium difficile is a Gram-positive, spore-forming anaerobic human gastrointestinal pathogen. C. difficile infection (CDI) is a major health concern worldwide, with symptoms ranging from diarrhea to pseudomembranous colitis, toxic megacolon, sepsis, and death. CDI onset and progression are mostly caused by intestinal dysbiosis and exposure to C. difficile spores. Current treatment strategies include antibiotics; however, antibiotic use is often associated with high recurrence rates and an increased risk of antibiotic resistance. Medium-chain fatty acids (MCFAs) have been revealed to inhibit the growth of multiple human bacterial pathogens. Components of coconut oil, which include lauric acid, have been revealed to inhibit C. difficile growth in vitro. In this study, we demonstrated that lauric acid exhibits potent antimicrobial activities against multiple toxigenic C. difficile isolates in vitro. The inhibitory effect of lauric acid is partly due to reactive oxygen species (ROS) generation and cell membrane damage. The administration of lauric acid considerably reduced biofilm formation and preformed biofilms in a dose-dependent manner. Importantly, in a mouse infection model, lauric acid pretreatment reduced CDI symptoms and proinflammatory cytokine production. Our combined results suggest that the naturally occurring MCFA lauric acid is a novel C. difficile inhibitor and is useful in the development of an alternative or adjunctive treatment for CDI.
Temporal structure of implicit motor imagery in visual hand‐shape discrimination as revealed by MEG

WE investigated the spatio-temporal brain activity on the time scale of several milliseconds related to the mental rotation task requiring judgements of hand orientation, using a whole-cortex MEG (magnetoencephalography) system. Neuronal activity in the visual cortex was observed ∼100–200 ms from stimulus onset, and that in inferior parietal lobe followed (after 200 ms). Both of these activities showed a contralateral dominance to visual stimulus hemifield. Premotor activity started later than the inferior parietal lobe activity, and these activities partially overlapped. Activity in primary motor and/or motosensory areas was observed in some subjects. The whole-cortex neuromagnetic measurements provided the time course of activity in the human brain associated with the implicit motor imagery: visual cortex ← inferior parietal lobe ↔ premotor cortex. This process is considered to be the transformation process of retinotopic locations into a body-centered reference frame necessary for the mental rotation task.
Instrumenting where it hurts: an automatic concurrent debugging technique

As concurrent and distributive applications are becoming more common and debugging such applications is very difficult, practical tools for automatic debugging of concurrent applications are in demand. In previous work, we applied automatic debugging to noise-based testing of concurrent programs. The idea of noise-based testing is to increase the probability of observing the bugs by adding, using instrumentation, timing "noise" to the execution of the program. The technique of finding a small subset of points that causes the bug to manifest can be used as an automatic debugging technique. Previously, we showed that Delta Debugging can be used to pinpoint the bug location on some small programs. In the work reported in this paper, we create and evaluate two algorithms for automatically pinpointing program locations that are in the vicinity of the bugs on a number of industrial programs. We discovered that the Delta Debugging algorithms do not scale due to the non-monotonic nature of the concurrent debugging problem. Instead we decided to try a machine learning feature selection algorithm. The idea is to consider each instrumentation point as a feature, execute the program many times with different instrumentations, and correlate the features (instrumentation points) with the executions in which the bug was revealed. This idea works very well when the bug is very hard to reveal using instrumentation, correlating to the case when a very specific timing window is needed to reveal the bug. However, in the more common case, when the bugs are easy to find using instrumentation points ranked high by the feature selection algorithm is not high enough. We show that for these cases, the important value is not the absolute value of the evaluation of the feature but the derivative of that value along the program execution path. As a number of groups expressed interest in this research, we built an open infrastructure for automatic debugging algorithms for concurrent applications, based on noise injection based concurrent testing using instrumentation. The infrastructure is described in this paper.
Efficient Computation of Sparse Hessians Using Coloring and Automatic Differentiation

The computation of a sparse Hessian matrix H using automatic differentiation (AD) can be made efficient using the following four-step procedure: (1) Determine the sparsity structure of H, (2) obtain a seed matrix S that defines a column partition of H using a specialized coloring on the adjacency graph of H, (3) compute the compressed Hessian matrix B ≡ HS, and (4) recover the numerical values of the entries of H from B. The coloring variant used in the second step depends on whether the recovery in the fourth step is direct or indirect: a direct method uses star coloring and an indirect method uses acyclic coloring. In an earlier work, we had designed and implemented effective heuristic algorithms for these two NP-hard coloring problems. Recently, we integrated part of the developed software with the AD tool ADOL-C, which has recently acquired a sparsity detection capability. In this paper, we provide a detailed description and analysis of the recovery algorithms and experimentally demonstrate the efficacy of the coloring techniques in the overall process of computing the Hessian of a given function using ADOL-C as an example of an AD tool. We also present new analytical results on star and acyclic coloring of chordal graphs. The experimental results show that sparsity exploitation via coloring yields enormous savings in runtime and makes the computation of Hessians of very large size feasible. The results also show that evaluating a Hessian via an indirect method is often faster than a direct evaluation. This speedup is achieved without compromising numerical accuracy.
Draft Genome Sequence of Hypervirulent and Vaccine Candidate Streptococcus suis Strain SC19

ABSTRACT Streptococcus suis, a zoonotic bacterium found primarily in pigs, has been recognized recently as an emerging pathogen of humans. Herein, we describe the genome of Streptococcus suis strain SC19, a hypervirulent and vaccine candidate strain isolated from a pig amid the 2005 outbreak in China.
An empirical study on requirements traceability using eye-tracking

Requirements traceability (RT) links help developers to understand programs and ensure that their source code is consistent with its documentation. Creating RT links is a laborious and resource-consuming task. Information Retrieval (IR) techniques are useful to automatically recover traceability links. However, IR-based approaches typically have low accuracy (precision and recall) and, thus, creating RT links remains a human intensive process. We conjecture that understanding how developers verify RT links could help improve the accuracy of IR-based approaches to recover RT links. Consequently, we perform an empirical study consisting of two controlled experiments. First, we use an eye-tracking system to capture developers' eye movements while they verify RT links. We analyse the obtained data to identify and rank developers' preferred source code entities (SCEs), e.g., class names, method names. Second, we use the ranked SCEs to propose two new weighting schemes called SE/IDF (source code entity/inverse document frequency) and DOI/IDF (domain or implementation/inverse document frequency) to recover RT links combined with an IR technique. SE/IDF is based on the developers preferred SCEs to verify RT links. DOI/IDF is an extension of SE/IDF distinguishing domain and implementation concepts. We use LSI combined with SE/IDF, DOI/IDF, and TF/IDF to show, using two systems, iTrust and Pooka, that LSIDOI/IDF statistically improves the accuracy of the recovered RT links over LSITF/IDF.
Comparing marine primary production estimates through different methods and development of conversion equations

Numerous studies have compared the rates of primary production using various techniques at specific locations and times. However, these comparisons are local and cannot be used to compare or scale rates of primary production using different methods across ocean basins or seasonal time scales. Here, we quantify the range in rates of primary production derived using different techniques and provide equations that allow conversions of estimates between different methods. We do so on the basis of a compilation of data on volumetric estimates of primary production rates concurrently estimated with at least two different methods. We observed that the comparison of estimates of marine phytoplankton primary production derived from different methods reveals very large variations between methods. The highest primary production estimates are derived using the 18O method, which may provide the best and more generally applicable estimate of gross primary production. The regression equations presented in this work provide the best available approach to convert data across methods and therefore integrate and synthesize available and future data derived using different methods.
EMANTIC I MAGE R ETRIEVAL USING RELEVANCE FEEDBACK

This paper presents optimized interactive content-based image retrieval framework based on AdaBoost learning method. As we know relevance feedback (RF) is online process, so we have optimized the learning process by considering the most positive image selection on each feedback iteration. To learn the system we have used AdaBoost. The main significances of our system are to address the small training sample and to reduce retrieval time. Experiments are conducted on 1000 semantic colour images from Corel database to demonstrate the effectiveness of the proposed framework. These experiments employed large image database and combined RCWFs and DT-CWT texture descriptors to represent content of the images.
Qualitative Research in Education

This accessible and practical book is a perfect quick guide for postgraduate researchers in education. Looking at the interdependence of teaching and research, the authors show that a critical and analytical exploration of policies and practices is a necessary part of what we mean by being a 'professional' in education. Drawing on the authors' substantial experience of teaching research skills at postgraduate level, as well as on their own experiences as active researchers, the book will guide you through: - discourse analysis - visual methods - textual research - data collection and analysis This co-authored book is structured around a range of methods applicable to educational research and appropriate for use by practitioners at all stages of their professional development. It takes recognisable, 'real life' scenarios as its starting point for each discussion of method, so that readers are able to start from the known and familiar. As well as exploring theoretical aspects of research method, each chapter provides practical tasks and points for discussion and reflection. These approaches, taken together, are designed to build confidence and encourage reader engagement and enjoyment.
ATP-sensitive K+ channels in renal mitochondria.

Isolated kidney mitochondria swell when incubated in hyposmotic solutions containing K+ salts in a manner inhibited by ATP, ADP, 5-hydroxydecanoate, and glibenclamide and stimulated by GTP and diazoxide. These results suggest the existence of ATP-sensitive K+ channels in these mitochondria, similar to those previously described in heart, liver, and brain. Renal mitochondrial ATP-sensitive K+ uptake rates are approximately 140 nmol.min-1.mg protein-1. This K+ transport results in a slight increase in respiration and decrease in the inner membrane potential. In addition, the activation of ATP-inhibited K+ uptake using diazoxide leads to a decrease of ATP hydrolysis through the reverse activity of the F0F1 ATP synthase when respiration is inhibited. In conclusion, we characterize an ATP-sensitive K+ transport pathway in kidney mitochondria that affects volume, respiration, and membrane potential and may have a role in the prevention of mitochondrial ATP hydrolysis.
Systemic therapy and the social relational model of disability: enabling practices with people with intellectual disability

Therapy has been critiqued for personalizing the political (Kitzinger, 1993). The social-relational model (Thomas, 1999) is one theoretical resource for understanding the practices of therapy through a political lens. The social model(s) have viewed therapy with suspicion. This paper highlights – using composite case examples and the authors primary therapeutic modality, systemic therapy – some systemic practices with adults with Intellectual Disability (ID) that enact a position that it is suggested have some coherence with and, may reciprocally, inform the social-relational model. The practice examples illustrate a support system at risk of disabling those it is mandated to support, the possibility of therapeutically ‘successful’ practices (including systemic practices) and disablement going hand in hand; as well as the psycho-emotional1 Thomas, 2006) consequences of the relational positions created by the service system. The paper concludes by suggesting that systemic conversations traversing culture, time and place can be a springboard to unearthing and challenging disabling ideas and practices.
Hémianopsie latérale homonyme : amputation du champ visuel, perception implicite et hallucinations visuelles

L’hemianopsie laterale homonyme (HLH) est une amputation du meme hemichamp visuel, pour chacun des deux yeux, a la suite d’une atteinte retro-chiasmatique. La perte de champ visuel est controlaterale a la lesion (c’est-a-dire qu’une lesion droite engendre une amputation des deux hemichamps visuels gauches : HLHg et inversement). Une HLH bilaterale realise une cecite centrale ou cecite corticale. L’HLH est le trouble visuel le plus frequent a la suite d’une atteinte cerebrale. L’etiologie la plus frequente est l’accident vasculaire cerebral. Elle est souvent associee a des difficultes de lecture, de reperage dans l’espace, d’exploration visuo-spatiale, d’acces a l’information dans sa globalite et a l’impossibilite de conduire une automobile. Il existe, cependant, des capacites visuelles non conscientes au sein du champ visuel dit « aveugle ». Ces capacites, decrites des le debut du xxe siecle, ont ete appelees par Weiskrantz en 1974 blindsight et leur correlat neuro-anatomique reste discute a l’heure actuelle. De plus, il n’est pas rare que les patients atteints d’une amputation du champ visuel d’origine centrale presentent dans leur champ visuel aveugle des hallucinations visuelles dont les mecanismes physiopathologiques restent meconnus. Enfin, nous avons pu mettre en evidence l’incidence de la lateralisation d’une lesion occipitale sur le traitement visuel en champ central des patients hemianopsiques a la fois d’un point de vue comportemental mais egalement a l’aide de l’IRMf. Ces recherches rejoignent le concept recent de sightblind, c’est-a-dire l’existence d’un trouble visuel dans le champ visuel voyant des patients hemianopsiques. De par la diversite des troubles neurovisuels observes chez les patients hemianopsiques, ce trouble constitue un modele pathologique de choix pour etudier le role complexe du cortex visuel primaire dans la vision. Il ne fait aucun doute que l’ensemble de ces recherches, comme nous le discutons ici, aura des repercussions importantes egalement sur le plan clinique.
LMO2 is required for TAL1 DNA binding activity and initiation of definitive haematopoiesis at the haemangioblast stage

Abstract LMO2 is a bridging factor within a DNA binding complex and is required for definitive haematopoiesis to occur. The developmental stage of the block in haematopoietic specification is not known. We show that Lmo2−/− mouse embryonic stem cells differentiated to Flk-1+ haemangioblasts, but less efficiently to haemogenic endothelium, which only produced primitive haematopoietic progenitors. Genome-wide approaches indicated that LMO2 is required at the haemangioblast stage to position the TAL1/LMO2/LDB1 complex to regulatory elements that are important for the establishment of the haematopoietic developmental program. In the absence of LMO2, the target site recognition of TAL1 is impaired. The lack of LMO2 resulted in altered gene expression levels already at the haemangioblast stage, with transcription factor genes accounting for ∼15% of affected genes. Comparison of Lmo2−/− with Tal1−/− Flk-1+ cells further showed that TAL1 was required to initiate or sustain Lmo2 expression.