Miracle-dz/UniFAR-FTUs huggingface dataset:
The Generation of Turnip Crinkle Virus-Like Particles in Plants by the Transient Expression of Wild-Type and Modified Forms of Its Coat Protein

Turnip crinkle virus (TCV), a member of the genus carmovirus of the Tombusviridae family, has a genome consisting of a single positive-sense RNA molecule that is encapsidated in an icosahedral particle composed of 180 copies of a single type of coat protein. We have employed the CPMV-HT transient expression system to investigate the formation of TCV-like particles following the expression of the wild-type coat protein or modified forms of it that contain either deletions and/or additions. Transient expression of the coat protein in plants results in the formation of capsid structures that morphologically resemble TCV virions (T = 3 structure) but encapsidate heterogeneous cellular RNAs, rather than the specific TCV coat protein messenger RNA. Expression of an amino-terminal deleted form of the coat protein resulted in the formation of smaller T = 1 structures that are free of RNA. The possibility of utilizing TCV as a carrier for the presentation of foreign proteins on the particle surface was also explored by fusing the sequence of GFP to the C-terminus of the coat protein. The expression of coat protein-GFP hybrids permitted the formation of VLPs but the yield of particles is diminished compared to the yield obtained with unmodified coat protein. Our results confirm the importance of the N-terminus of the coat protein for the encapsidation of RNA and show that the coat protein's exterior P domain plays a key role in particle formation.
In vivo assessment of stent expansion and recoil in normal porcine coronary arteries: differential outcome by stent design.

BACKGROUND Despite the routine use of high pressure, coronary stents generally fail to achieve a cross-sectional area (CSA) >60% to 80% of the nominal CSA of their dilating balloon. The extent to which incomplete balloon expansion and postdeflation stent recoil contribute to this failure has not been fully evaluated. METHODS AND RESULTS Thirty-two stents (8 Gianturco-Roubin II, 8 Palmaz-Schatz, 8 MultiLink, and 8 NIR) were deployed in nondiseased coronary arteries of 8 Yorkshire pigs. All stents were then expanded according to 1 of 3 balloon strategies: appropriately sized compliant balloons, oversized compliant balloons, or oversized noncompliant balloons. Continuous ultrasound imaging was performed during stepwise balloon inflation and deflation, with an 0.018-in imaging core positioned within the guidewire lumen of the balloon. In these normal arteries, balloon underexpansion relative to the nominal size was not observed. After balloon deflation, however, all stents showed significant recoil from their maximum inflated CSA. Recoil was significantly greater for the coil Gianturco-Roubin II stent (30% CSA) than for the 3 slotted-tube stent designs (15% to 17% CSA). CONCLUSIONS In normal, compliant coronary arteries, stent recoil is the predominant mechanism by which stents fail to achieve the nominal CSA of their dilating balloon. The magnitude of this in vivo stent recoil is significantly greater than reported from bench testing and varies with stent design (coil versus slotted tube). Postdilatation strategies that result in controlled stent overexpansion are needed to overcome this recoil phenomenon and result in a final stent CSA that approximates the reference artery CSA.
Graphical Perception in Animated Bar Charts

Interactive visual applications create animations that encode changes in the data. For example, cross-filtering dynamically updates linked visualizations based on the user's continuous brushing actions. The animated effects resulting from these interactions depends both on how interaction (e.g., brushing speed) controls properties of the animation such as frame rate, as well as how the data that is being explored dictates the data encoded in the animation. Past work has found that frame rate matters to general perception, however a critical question is which of these animation and data properties affects the perceptual accuracy of judgement tasks, and to what extent. Although graphical perception has been well studied for static data visualizations, it is ripe for exploration in the animated setting. We designed two animated judgment tasks of a target bar in an animated bar chart and empirically evaluate the effects of 2 animations properties - highlighting of the target bar and frame rate - as well as 3 data properties that affect the target bar's value throughout the animation. In short, we find that the rate and timing of animation changes is easier detected in larger values; that encodings such as color are easier to detect than shapes; and that timing is important - earlier changes were harder to perceive as compared to later changes in the animation. Our results are an initial step to understanding perceptual accuracy for animated data visualizations, both for presentations and ultimately as part of interactive applications.
Multiresolution Random Accessible Mesh Compression

This paper presents a novel approach for mesh compression, which we call multiresolution random accessible mesh compression. In contrast to previous mesh compression techniques, the approach enables us to progressively decompress an arbitrary portion of a mesh without decoding other non‐interesting parts. This simultaneous support of random accessibility and progressiveness is accomplished by adapting selective refinement of a multiresolution mesh to the mesh compression domain. We present a theoretical analysis of our connectivity coding scheme and provide several experimental results. The performance of our coder is about 11 bits for connectivity and 21 bits for geometry with 12‐bit quantization, which can be considered reasonably good under the constraint that no fixed neighborhood information can be used for coding to support decompression in a random order.
RECRUITING AND DEVELOPING STRONG TEACHERS: A CASE STUDY OF SOUTH ASIA

Globalisation has an ongoing impact on education and learning systems, and so the roles and responsibilities of teachers are constantly in flux. Teachers are not just responsible for students’ intellectual development but also for imparting a broad range of skills to allow students to fully participate in a competitive, information-based global society. In many developing and emerging economies, these changes have created a demand for foreign curriculum and assessment systems. South Asia, in particular, has seen an increase in the number of English medium private schools that offer the British curriculum. Mostly local teachers in these schools are in a unique situation: they have been trained for national education systems but are expected to deliver an international curriculum and prepare local students for foreign qualification exams using English as the medium of instruction, a second or third language for their students. The schools that form British Council’s Partner Schools Global Network (PSGN) are examples of this: the network connects international and English-medium schools globally to form ‘a community of schools’ that offer a British curriculum. This paper will discuss the results of a study in South Asia which looks at the current situation of teacher training and capacity development in secondary schools within the PSGN in South Asia. The key areas of teacher training and capacity development under consideration will include, but not be limited to induction and preparation, learning and development, rewards and recognition, and occupational motivation. The findings of the research will identify the global best practices and progresses in areas of secondary teacher training and capacity development and also facilitate in understanding the motivations and decision-making practices of school leaders and principals behind opting for certain approaches. In case any significant gaps are identified, interventions and recommendations will be proposed to enhance the capacity of secondary teachers within the PSGN, which may also be replicable for teachers working in similar contexts.
Fallacious Results from Measuring Salivary Carbamazepine Concentrations

Summary During a carbamazepine (CBZ) relative bioavailability study involving tablets and a syrup preparation, salivary drug concentrations appeared disproportionately high relative to simultaneous plasma drug concentrations in the first 2–3 h after oral drug intake. This raised the suspicion of contamination of saliva by retention of drug in the mouth. In a separate study CBZ was retained in the mouth in tablet form (whole or crushed) or in syrup, for only 5 s before being spat out, and the mouth was carefully rinsed. Despite this, measurable salivary concentrations, sufficient to cause substantial error if extrapolated to simultaneous plasma drug concentrations, were present for at least 2 h after drug administration. CBZ in these studies disappeared from saliva with an apparent mean half-life of 21.0 ± 4.8 min. This experience suggests that, in therapeutic drug monitoring, salivary CBZ concentrations for at least 2 h after dosage may lead to invalid conclusions about simultaneous plasma CBZ concentrations.
I-DIRECTIONAL MODULATION OF BED NUCLEUS OF STRIA ERMINALIS NEURONS BY 5-HT : MOLECULAR EXPRESSION AND UNCTIONAL PROPERTIES OF EXCITATORY 5-HT RECEPTOR

bstract—Activation of neurons in the anterolateral bed nuleus of the stria terminalis (BNSTALG) plays an important role in ediating the behavioral response to stressful and anxiogenic timuli. Application of 5-HT elicits complex postsynaptic reponses in BNSTALG neurons, which includes (1) membrane yperpolarization (5-HTHyp), (2) hyperpolarization followed by epolarization (5-HTHyp-Dep), (3) depolarization (5-HTDep) or (4) o response (5-HTNR). We have shown that the inhibitory esponse is mediated by activation of postsynaptic 5-HT1A eceptors. Here, we used a combination of in vitro whole-cell atch-clamp recording and single cell reverse transcriptase olymerase chain reaction (RT–PCR) to determine the pharacological properties and molecular profile of 5-HT recepor subtypes mediating the excitatory response to 5-HT in NSTALG neurons. We show that the depolarizing component f both the 5-HTHyp/Dep and the 5-HTDep response was medited by activation of 5-HT2A, 5-HT2C and/or 5-HT7 receptors. ingle cell RT–PCR data revealed that 5-HT7 receptors (46%) nd 5-HT1A receptors (41%) are the most prevalent receptor ubtypes expressed in BNSTALG neurons. Moreover, 5-HT eceptor subtypes are differentially expressed in type I–III NSTALG neurons. Hence, 5-HT2C receptors are almost excluively expressed by type III neurons, whereas 5-HT7 recepors are expressed by type I and II neurons, but not type III eurons. Conversely, 5-HT2A receptors are found predomiantly in type II neurons. Finally, bi-directional modulation f individual neurons occurs only in type I and II neurons. ignificantly the distribution of 5-HT receptor subtypes in NSTALG neurons predicted the observed expression pattern f 5-HT responses determined pharmacologically. Together, hese results suggest that 5-HT can differentially modulate he excitability of type I–III neurons, and further suggest that
Usefulness of CHROMagar Candida Medium, Biochemical Methods – API ID32C and VITEK 2 Compact and Two MALDI-TOF MS Systems for Candida spp. Identification

Abstract This study was conducted to compare of the yeasts identification results obtained with two new systems using the MALDI-TOF MS technique with the ones obtained using the routine identification methods of Candida spp. in clinical microbiology laboratories. All 124 Candida spp. isolates were recovered from the routine examination of clinical specimens in microbiological laboratories and collected in the Centre of Quality Control in Microbiology in Warsaw (Poland). Our findings confirm the high agreement (98%) of fungal identification using the standard, biochemistry laboratory methods and mass spectrometry technique.
Reply to ‘Interpretation of concordance measures for clustered data’

We thank the authors of the letter to the editor [1] for their insightful comments on our paper on concordance measures in shared frailty models [2]. We intend here to answer some questions and to clarify related issues concerning the interpretation and the use of concordance measures in the context of clustered data. Concerning the interpretation of the Gönen and Heller estimator, we agree that the interpretation should be done cautiously as it supposed that the Cox prognostic model used is correct, and the regression parameters are well estimated. This was previously mentioned in the discussion of our original paper [2]. We thank Van Klaveren et al. for bringing new input with simulation results. In a second point, they suggested that using the validation data to estimate the frailties of new cluster in conditional predictions prevents for external validation and should be seen as a form of an internal validation. However, the frailties can be seen as unobservable covariates. Thus, in the same way than doing prediction validation in new dataset requires to use the covariate of patients from the new dataset it seems natural to derive new frailties for the new group using observed information from the new group. These new frailties are derived conditionally from the values of the covariates in the validation population but both the variance and the covariate effects ˇ are estimated on the development population (see formula (1) of our article [2]). Only the covariates are taken from the validation population. Thus, if it is correct that marginal prediction can be used and can be useful, as shown in [3], we think that conditional predictions are also adequate to do external validation on an independent dataset. In the discussion, we stated that ‘Making conditional prediction on new groups illustrates the ability of the proposed method to externally validate the prediction model. ’ This sentence illustrates the fact that it is possible (but not required) to investigate external validation using the prediction of the random effect on new groups. Finally, care must be taken in keeping same frailties to do some temporal validation, as frailties can evolve with time, even in a given cluster. Considering the use of within or between-cluster measures only, we think it is always interesting to give both. The two give interesting information, and the comparison of the two measures can bring additional information, for example, on the impact of the frailty term on the prediction. We take advantage of this response to clarify that, as specified by Van Oirbeek and Lesaffre [4] and in the section method of our paper, the within concordance is the same in the conditional and marginal level. Only the between-cluster measure differs, and even if it is not used to take some final decision, it is still interesting to display.
Efficient probabilistic Range-Only SLAM

This work addresses range-only SLAM (RO-SLAM) as the Bayesian inference problem of sequentially tracking a vehicle while estimating the location of a set of beacons without any prior information. The only assumptions are the availability of odometry and a range sensor able of identifying the different beacons. We propose exploiting the conditional independence between the position distributions of each beacon within a Rao-Blackwellized Particle Filter (RBPF) for maintaining independent Sum of Gaussians (SOGs) for each beacon. Unlike other approaches, it is shown then that a proper probabilistic observation model can be derived for online operation with no need for delayed initializations. We provide a rigorous statistical comparison of this proposal with previous work of the authors where a Monte-Carlo approximation was employed instead for the conditional densities. As verified experimentally, this new proposal represents a significant improvement in accuracy, computation time, and robustness against outliers.
Named Entity Recognition for Ukrainian: A Resource-Light Approach

A cooling system for an electron microscope specimen comprises a refrigerant container, a passage for introducing the refrigerant into a heat-exchanging position, a flow rate-adjusting valve mounted in an exhaust passage and a control unit. The flow rate of gas produced by evaporation is adjusted by a rate-adjusting valve. The control unit establishes either a maximum flow rate mode for rapid cooling or a minimum flow rate mode for observation of an image.
Applying Pairwise Ranked Optimisation to Improve the Interpolation of Translation Models

In Statistical Machine Translation we often have to combine different sources of parallel training data to build a good system. One way of doing this is to build separate translation models from each data set and linearly interpolate them, and to date the main method for optimising the interpolation weights is to minimise the model perplexity on a heldout set. In this work, rather than optimising for this indirect measure, we directly optimise for BLEU on the tuning set and show improvements in average performance over two data sets and 8 language pairs.
Determining the Effective Sample Size of a Parametric Prior

Summary We present a definition for the effective sample size of a parametric prior distribution in a Bayesian model, and propose methods for computing the effective sample size in a variety of settings. Our approach first constructs a prior chosen to be vague in a suitable sense, and updates this prior to obtain a sequence of posteriors corresponding to each of a range of sample sizes. We then compute a distance between each posterior and the parametric prior, defined in terms of the curvature of the logarithm of each distribution, and the posterior minimizing the distance defines the effective sample size of the prior. For cases where the distance cannot be computed analytically, we provide a numerical approximation based on Monte Carlo simulation. We provide general guidelines for application, illustrate the method in several standard cases where the answer seems obvious, and then apply it to some nonstandard settings.
Adaptive Least Mean Squares Estimation of Graph Signals

The aim of this paper is to propose a least mean squares (LMS) strategy for adaptive estimation of signals defined over graphs. Assuming the graph signal to be band-limited, over a known bandwidth, the method enables reconstruction, with guaranteed performance in terms of mean-square error, and tracking from a limited number of observations over a subset of vertices. A detailed mean square analysis provides the performance of the proposed method, and leads to several insights for designing useful sampling strategies for graph signals. Numerical results validate our theoretical findings, and illustrate the performance of the proposed method. Furthermore, to cope with the case where the bandwidth is not known beforehand, we propose a method that performs a sparse online estimation of the signal support in the (graph) frequency domain, which enables online adaptation of the graph sampling strategy. Finally, we apply the proposed method to build the power spatial density cartography of a given operational region in a cognitive network environment.
Automatic substitute CT generation and contouring for MRI-alone external beam radiation therapy from standard MRI sequences

Purpose: Validation of automatic substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans for MR-Sim prostate treatment planning. Methods and Materials: A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence was acquired. Three additional small field of view scans were acquired: T2w, T2*w and T1w flip angle 800 for gold fiducials. Patients received a routine planning CT scan. Manual contouring of the prostate, rectum, bladder and bones was performed independently on the CT and MR scans. Three experienced observers contoured each organ on MRI allowing inter-observer quantification. To generate a training database, each patient CT scan was co-registered to their whole pelvis T2w using symmetric rigid registration and structure guided deformable registration. A new multi-atlas local weighted voting method was used to generate automatic contours and sCT results. Results: The mean error in Hounsfield units (HU) between the sCT and corresponding patient CT (within the body contour) was 0.6±14.7 (mean±1 SD) with a mean absolute M AN US CR IP T AC CE PT ED ACCEPTED MANUSCRIPT
Universal Plans for Reactive Robots in Unpredictable Environments

To date, reactive robot behavior has been achieved only through manual programming. This paper describes a new kind of plan, called a "universal plan", which can be synthesized automatically, yet generates appropriate behavior in unpredictable environments. In classical planning work, problems were posed with unique initial and final world states; in my approach a problem specifies only a goal condition. The planner is thus unable to commit to any specific future course of events but must specify appropriate reactions for anticipated situations. An alternative conception is that one universal plan compactly represents every classical plan. Which part of the universal plan is executed depends entirely on how the environment behaves at execution time. Universal plans are constructed from state-space operator schemas by a nonlinear planner. They explicitly identify predicates requiring monitoring at each moment of execution, and provide for sabotage, serendipity and failure without requiring replanning.
A random polynomial time algorithm for approximating the volume of convex bodies

We present a randomised polynomial time algorithm for approximating the volume of a convex body <italic>K</italic> in <italic>n</italic>-dimensional Euclidean space. The proof of correctness of the algorithm relies on recent theory of rapidly mixing Markov chains and isoperimetric inequalities to show that a certain random walk can be used to sample nearly uniformly from within <italic>K</italic>.
Model reduction for linear bayesian system identification

Bayesian estimation methods have been recently introduced in the system identification community. When applied in this context, they allow to estimate the unknown system in terms of its impulse response coefficients, thus returning a model with high (possibly infinite) McMillan degree. In this paper we discuss how these Bayesian estimation techniques can be equipped with a completely automatic model reduction procedure, in order to obtain a low McMillan degree model as a final estimate. Besides being more suitable for filtering and control applications, low-order models seem also to better capture the dynamics of the systems to be identified, as demonstrated by the extensive Monte Carlo experiments which are included in this paper.
Identifying the relevant frames of reference in programming by demonstration using task-parameterized Gaussian mixture regression

Automatic identification of the relevant frames of references (or external task parameters) in programming by demonstration using the task-parameterized Gaussian mixture regression (TP-GMM) is addressed in this paper. While performing a given task, there may be several external task parameters, some of which are relevant to the specific task, while some others are not relevant. Identifying the irrelevant task parameters could help to automatize the selection of task parameters, construct a more compact model of the task and achieve better performances in the reproduction phase. At first, all the potential candidate frames of references will be taken into account, then, after identifying the irrelevant ones, they will be removed from the model, and only the relevant frames will be used for the reproduction. The performance of the approach is testified through an experiment, where the reproduction with only the relevant frames of references provides much better results compared to the case of including all candidate frames of references.