Miracle-dz/UniFAR-FTUs huggingface dataset:
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets

We propose an image representation scheme combining the local and nonlocal characterization of patches in an image. Our representation scheme can be shown to be equivalent to a tight frame constructed from convolving local bases (e.g., wavelet frames, discrete cosine transforms, etc.) with nonlocal bases (e.g., spectral basis induced by nonlinear dimension reduction on patches), and we call the resulting frame elements convolution framelets. Insight gained from analyzing the proposed representation leads to a novel interpretation of a recent high-performance patch-based image processing algorithm using the point integral method (PIM) and the low dimensional manifold model (LDMM) [S. Osher, Z. Shi, and W. Zhu, Low Dimensional Manifold Model for Image Processing, Tech. Rep., CAM report 16-04, UCLA, Los Angeles, CA, 2016]. In particular, we show that LDMM is a weighted $\ell_2$-regularization on the coefficients obtained by decomposing images into linear combinations of convolution framelets; based on this u.
Genome-wide functional genetic screen with the anticancer agent AMPI-109 identifies PRL-3 as an oncogenic driver in triple-negative breast cancers

Triple-negative breast cancers (TNBC) are among the most aggressive and heterogeneous cancers with a high propensity to invade, metastasize and relapse. Here, we demonstrate that the anticancer compound, AMPI-109, is selectively efficacious in inhibiting proliferation and inducing apoptosis of multiple TNBC subtype cell lines as assessed by activation of pro-apoptotic caspases-3 and 7, PARP cleavage and nucleosomal DNA fragmentation. AMPI-109 had little to no effect on growth in the majority of non-TNBC cell lines examined. We therefore utilized AMPI-109 in a genome-wide shRNA screen in the TNBC cell line, BT-20, to investigate the utility of AMPI-109 as a tool in helping to identify molecular alterations unique to TNBC. Our screen identified the oncogenic phosphatase, PRL-3, as a potentially important driver of TNBC growth, migration and invasion. Through stable lentiviral knock downs and transfection with catalytically impaired PRL-3 in TNBC cells, loss of PRL-3 expression, or functionality, led to substantial growth inhibition. Moreover, AMPI-109 treatment, downregulation of PRL-3 expression or impairment of PRL-3 activity reduced TNBC cell migration and invasion. Histological evaluation of human breast cancers revealed PRL-3 was significantly, though not exclusively, associated with the TNBC subtype and correlated positively with regional and distant metastases, as well as 1 and 3 year relapse free survival. Collectively, our study is proof-of-concept that AMPI-109, a selectively active agent against TNBC cell lines, can be used as a molecular tool to uncover unique drivers of disease progression, such as PRL-3, which we show promotes oncogenic phenotypes in TNBC cells.
Ultramicro method for determination of iron in serum with the graphite furnace.

An ultramicro method is described for determining iron in 50 µl of serum. Hot trichloroacetic acid is used to remove protein and hemoglobin iron, and atomic absorption analysis of 10 µl of the supernatant fluid is carried out with use of a graphite furnace and a specially grooved graphite tube. Results correlate well with those obtained by a conventional flame atomic absorption method for iron that requires a 1-ml sample of serum. A standard graphite tube can be used if the trichloroacetic acid extract is first diluted with water, but we rejected this procedure because of the extra time and effort involved and because of the increased problem of artifactual contamination with iron. When serum was analyzed with no pretreatment, results were higher, probably because of hemoglobin iron present in serum, even serum with no visible hemolysis.
Alternating skills training and clerkships to ease the transition from preclinical to clinical training

Background: The transition from preclinical to clinical training is perceived as stressful with a high workload being the main difficulty. To ease this transition, we implemented a dual learning year, where just-in-time skills training and clerkships alternated. Aims: To examine the effect of the dual learning year on students’ stress and perceptions of workload and skills level, and to compare these data with a baseline measurement from a curriculum in which skills training was provided in advance of clerkships. Method: During the first Master year, students completed four rotations in which 5 weeks of skills training and 5-week clerkships alternated. In the second clerkship week of each rotation, students (n = 476) completed questionnaires measuring their experienced workload, perceived skills level and stress. Analysis of variance was used for trend analysis and to determine differences with the baseline measurement (n = 83). Results: During the dual learning year, ‘experienced workload’ decreased (F(1,471) = 9.408, p < 0.01), ‘perceived skills level’ increased (F(1,471) = 94.202, p < 0.001) and stress decreased (F(1,471) = 3.309, p < 0.10). ‘Experienced workload’ was lower (F(5,553) = 7.599, p < 0.001) and ‘perceived skills level’ was comparable to the baseline measurement. Conclusions: Compared to the baseline measurement and the results of earlier studies on transition difficulties, alternating just-in-time skills training and clerkships seem to ease the transition from preclinical to clinical training.
Dimension Estimation Using Random Connection Models

Information about intrinsic dimension is crucial to perform dimensionality reduction, compress information, design efficient algorithms, and do statistical adaptation. In this paper we propose an estimator for the intrinsic dimension of a data set. The estimator is based on binary neighbourhood information about the observations in the form of two adjacency matrices, and does not require any explicit distance information. The underlying graph is modelled according to a subset of a specific random connection model, sometimes referred to as the Poisson blob model. Computationally the estimator scales like n log n, and we specify its asymptotic distribution and rate of convergence. A simulation study on both real and simulated data shows that our approach compares favourably with some competing methods from the literature, including approaches that rely on distance information.
Autophagy and Human Parturition: Evaluation of LC3 Expression in Placenta from Spontaneous or Medically Induced Onset of Labor

Induction of labor is one of the most used procedures in obstetrics, performed to achieve vaginal delivery through cervical ripening and stimulation of uterine contractions. We investigated the impact of induction of labor upon placental autophagy, a catabolic pathway activated in response to alteration of the physiological intracellular conditions. We collected 28 singleton placentas at the time of uncomplicated term vaginal delivery (7 spontaneous onset of labor, 21 induced labor). Autophagy was evaluated by immunohistochemistry, immunofluorescence, and immunoblotting. No significant difference in the autophagy expression was found between spontaneous or induced onset of labor. We found an inverse relationship between autophagy expression and the maternal prepregnancy body mass index, irrespective of the mode of labor onset. This result could be related to the nutritional maternal habits before and throughout pregnancy rather than rapid metabolic changes during labor.
Quality Characteristics of Sponge Cake Added with Leek(Allium tuberosum Rottler) Powder

Abstract This study was performed to investigate the quality characteristics of sponge cake made with leek(Allium tuberosum Rottler) powder. In order to evaluate the physical and sensory properties of different cake, the leek powder was added to wheat flour at various ratios(3, 5, 7, 9%, w/w). The specific gravity of bread dough tends to increase with the addition of leek powder. The moisture levels of the sponge cakes made with leek powder were higher than that of the control. Crumb color values, lightness(L) and redness(a) decreased by leek powder addition, while yellowness(b) was significantly increased (p<0.05). In texture analyses, hardness, cohesiveness, springiness and gumminess decreased with the addition of leek powder. In sensory evaluations, the 3% leek powder sponge cake showed higher sensory property scores than others(p<0.05). Key words: sponge cake, Allium tuberosum Rottler, texture, color value, sensory evaluation. † Corresponding author: Kyung-Ryun Cho, Dept. of Food and Nutrition, Hanyang Woman's College, Seoul 133-793, Korea. Tel: +82-2-2290-2189, Fax: +82-2-2290-2199, E-mail: krcho@hywoman.ac. kr
Natural Occurrence of Ochratoxin A in Musts, Wines and Grape Vine Fruits from Grapes Harvested in Argentina

In this study, ochratoxin A (OTA) occurrence in Argentinean musts, wines and dried vine fruits was evaluated, alongside with the performance of OchraStarTM columns for OTA extraction. In all the three matrices analyzed, the OchraStarTM columns showed good performance. The analysis of natural occurrence of OTA in the red must and the red wine samples showed low incidence with low levels of mean OTA contamination (0.12 ng/mL and 0.37 ng/mL, respectively), while 60% of the dried vine fruit samples were contaminated with OTA, in levels ranging from 0.26 to 20.28 ng/g.
Definitive Hosts of Versteria Tapeworms (Cestoda: Taeniidae) Causing Fatal Infection in North America

We previously reported fatal infection of a captive Bornean orangutan with metacestodes of a novel taeniid tapeworm, Versteria sp. New data implicate mustelids as definitive hosts of these tapeworms in North America. At least 2 parasite genetic lineages circulate in North America, representing separate introductions from Eurasia.
Boosting 3-D-Geometric Features for Efficient Face Recognition and Gender Classification

We utilize ideas from two growing but disparate ideas in computer vision-shape analysis using tools from differential geometry and feature selection using machine learning-to select and highlight salient geometrical facial features that contribute most in 3-D face recognition and gender classification. First, a large set of geometries curve features are extracted using level sets (circular curves) and streamlines (radial curves) of the Euclidean distance functions of the facial surface; together they approximate facial surfaces with arbitrarily high accuracy. Then, we use the well-known Adaboost algorithm for feature selection from this large set and derive a composite classifier that achieves high performance with a minimal set of features. This greatly reduced set, consisting of some level curves on the nose and some radial curves in the forehead and cheeks regions, provides a very compact signature of a 3-D face and a fast classification algorithm for face recognition and gender selection. It is also efficient in terms of data storage and transmission costs. Experimental results, carried out using the FRGCv2 dataset, yield a rank-1 face recognition rate of 98% and a gender classification rate of 86% rate.
An Improved Simple Method for Imaging the Shape of Complex Targets

The linear sampling method (LSM) is a simple and effective approach to image the shape of an unknown target through the solution of a linear equation whose known term is the field radiated by an elementary (i.e., monopolar) source located in a set of test points. In this paper, we extend the LSM formulation by generalizing the right-hand side of the equation to higher order multipoles. In particular, we discuss which is the expected method's outcome after such a change and propose a post-processing scheme to combine the results obtained for different multipoles. As shown with simulated and experimental data, the proper combination of higher order multipoles allows to achieve better images of complex shaped targets as compared to the standard LSM and to overcome some of its limitations.
Phonological sensitivity and the acquisition of new words in children.

Two studies are reported which aimed to examine the relationship between phonological sensitivity and the acquisition of new words that systematically differed in the familiarity of their sound structures. In the first study measures of phonological sensitivity, phonological short-term memory, vocabulary, and nonverbal ability were administered to forty-one 5-year-old children. Phonological sensitivity was related to the paired-associate learning of phonologically unfamiliar words, but not to the learning of familiar words. In the second study a group of 14 nonreading 5-year-old children received phonological sensitivity training. A control group was trained in semantic categorization. After the training, the phonological sensitivity group did perform better on measures of letter knowledge and phonological sensitivity (rhyme and first-sound categorization) and appeared to learn phonologically unfamiliar words more easily. The findings of both studies suggest that phonological sensitivity can support the acquisition of novel words.
High throughput gene expression profiling: a molecular approach to integrative physiology

Integrative physiology emphasizes the importance of understanding multiple pathways with overlapping, complementary, or opposing effects and their interactions in the context of intact organisms. The DNA microarray technology, the most commonly used method for high‐throughput gene expression profiling, has been touted as an integrative tool that provides insights into regulatory pathways. However, the physiology community has been slow in acceptance of these techniques because of early failure in generating useful data and the lack of a cohesive theoretical framework in which experiments can be analysed. With recent advances in both technology and analysis, we propose a concept of multidimensional integration of physiology that incorporates data generated by DNA microarray and other functional, genomic, and proteomic approaches to achieve a truly integrative understanding of physiology. Analysis of several studies performed in simpler organisms or in mammalian model animals supports the feasibility of such multidimensional integration and demonstrates the power of DNA microarray as an indispensable molecular tool for such integration. Evaluation of DNA microarray techniques indicates that these techniques, despite limitations, have advanced to a point where the question‐driven profiling research has become a feasible complement to the conventional, hypothesis‐driven research. With a keen sense of homeostasis, global regulation, and quantitative analysis, integrative physiologists are uniquely positioned to apply these techniques to enhance the understanding of complex physiological functions.
MCMC-Based Image Reconstruction with Uncertainty Quantification

The connection between Bayesian statistics and the technique of regularization for inverse problems has been given significant attention in recent years. For example, Bayes' law is frequently used as motivation for variational regularization methods of Tikhonov type. In this setting, the regularization function corresponds to the negative-log of the prior probability density; the fit-to-data function corresponds to the negative-log of the likelihood; and the regularized solution corresponds to the maximizer of the posterior density function, known as the maximum a posteriori (MAP) estimator of the unknown, which in our case is an image. Much of the work in this direction has focused on the development of techniques for efficient computation of MAP estimators (or regularized solutions). Less explored in the inverse problems community, and of interest to us in this paper, is the problem of sampling from the posterior density. To do this, we use a Markov chain Monte Carlo (MCMC) method, which has previously .
A plant pathogen reduces the enemy–free space of an insect herbivore on a shared host plant

An important mechanism in stabilizing tightly linked host–parasitoid and prey–predator interactions is the presence of refuges that protect organisms from their natural enemies. However, the presence and quality of refuges can be strongly affected by the environment. We show that infection of the host plant Silene latifolia by its specialist fungal plant pathogen Microbotryum violaceum dramatically alters the enemy–free space of a herbivore, the specialist noctuid seed predator Hadena bicruris, on their shared host plant. The pathogen arrests the development of seed capsules that serve as refuges for the herbivore's offspring against the specialist parasitoid Microplitis tristis, a major source of mortality of H. bicruris in the field. Pathogen infection resulted both in lower host–plant food quality, causing reduced adult emergence, and in two–fold higher rates of parasitism of the herbivore. We interpret the strong oviposition preference of H. bicruris for uninfected plants in the field as an adaptive response, positioning offspring on refuge–rich, high–quality hosts. To our knowledge, this is the first demonstration that plant–inhabiting micro–organisms can affect higher trophic interactions through alteration of host refuge quality. We speculate that such interference can potentially destabilize tightly linked multitrophic interactions.
A Discourse Copying Algorithm for Ellipsis and Anaphora Resolution

We give an analysis of ellipsis resolution in terms of a straightforward discourse copying algorithm that correctly predicts a wide range of phenomena. The treatment does not suffer from problems inherent in identity-of-relations analyses. Furthermore, in contrast to the approach of Dalrymple et al. [1991], the treatment directly encodes the intutive distinction between full NPs and the referential elements that corefer with them through what we term role linking. The correct predictions for several problematic examples of ellipsis naturally result. Finally, the analysis extends directly to other discourse copying phenomena.
Self-Other Differences in Perceiving Why People Eat What They Eat

People often view themselves more favorably than others, displaying unrealistic optimism. In the present study, we investigated whether people perceive their reasons for eating as better than those of others. Furthermore, we investigated which mechanisms of inaccuracy might underlie a possible bias when perceiving why people eat what they eat. In Study 1, 117 participants rated the social desirability of eating motives. In Study 2, 772 participants provided information on their own and others’ motives for eating behavior. In Study 1, particularly desirable motives were eating because of hunger, health reasons, and liking. Particularly undesirable motives were eating to make a good impression, to comply with social norms, and to regulate negative affect. Study 2 revealed that for socially desirable motives, participants perceived their own motives to be stronger; for undesirable motives, the opposite pattern emerged, with others being attributed stronger motives. Moreover, the perception of others’ emotional and social motives varied with participants’ own healthy eating behavior. Since the perception of eating motives of others should be independent of one’s own behavior, this pattern of results indicates a relative inaccuracy in the perception of others’ eating motives. In conclusion, there is evidence for unrealistic optimism in eating motives. For social and emotional motives, this self-favoring view seems to be driven by a relatively inaccurate perception of others.
Corpus-Driven Generation of Weather Forecasts

In traditional natural language generation (NLG), careful analysis of a corpus of example texts and determining the single correct sublanguage behind it is seen a s one of the main tasks of the NLG system builder. In practice, this often means elimination of varia tion in the corpus and specification of conditions for rule application to the point where an NLG system be comes (virtually) deterministic. This approach is time-consuming, does not apply objective criteri a for deciding what is correct, and contributes to the lack of robustness and reusable components in NLG. Mor eove , with variation regarded as a ‘bug’ to be eliminated, systems run the risk of implementing a subj ective or restrictive view of the domain sublanguage. This research note argues that relative frequ ency provides an objective, easily applicable tool for dealing with corpus variation. The probabilistic a pproach to NLG can also help cut down on manual corpus analysis, make systems more robust and compon ents more reusable. A methodology is described that combines use of a base generator with a separa te, utomatically adaptable, probabilistic decision-making component. Three different decision-mak ing techniques are compared and evaluated with a focus on their ability to model idiolectal variation.
Evaluation of a new multi-parallel line immunoassay for systemic sclerosis-associated antibodies in an Asian population.

OBJECTIVES To compare the SSc-line immunoassay (LIA) with conventional techniques of antibody detection, to evaluate its diagnostic utility and to describe clinical associations of antibodies in Asian SSc patients. METHODS Stored sera from patients with SSc (n = 68), SLE (n = 49), OA (n = 41) and normal controls (NCs, n = 32) were evaluated. Cohen's κ and Bland-Altman plots were used to evaluate agreement. RESULTS There was good agreement between LIA and ELISA for anti-Scl-70 (κ = 0.97), anti-CENPA (κ = 0.83), anti-CENPB (κ = 0.96) and anti-PmScl100 (κ = 1.00) (5.48-8.22% of values outside the 95% limits of agreement using Bland-Altman plots), and between LIA and IIF for anti-CENPA (κ = 0.81) and anti-CENPB (κ = 0.77) (P < 0.001). Using LIA, of 32 (32/68, 47%) SSc patients negative for anti-Scl-70 and anti-CENPA/B, 5 (5/32, 15%) were positive for anti-Ku, -Nor90, -fibrillarin and -RP155. Specificity of each antibody for SSc was at least 97% (vs OA/NC) and 94% (vs SLE), except for anti-Ro52 (63%). Anti-CENPB was associated with joint pain [odds ratio (OR) 0.17], interstitial lung disease (OR 0.24) and telangiectasia (OR 4.00) (P < 0.05). Anti-Ro60 was associated with pulmonary arterial hypertension (OR 3.89, P = 0.041). CONCLUSION The SSc-LIA has good agreement with conventional techniques for selected antibodies and has good diagnostic utility.
The splicing regulators Tra and Tra2 are unusually potent activators of pre-mRNA splicing

Sexual differentiation in Drosophila is regulated through alternative splicing of doublesex. Female-specific splicing is activated through the activity of splicing enhancer complexes assembled on multiple repeat elements. Each of these repeats serves as a binding platform for the cooperative assembly of a heterotrimeric complex consisting of the SR proteins Tra, Tra2 and 9G8. Using quantitative kinetic analyses, we demonstrate that each component of the enhancer complex is capable of recruiting the spliceosome. Surprisingly, Tra, Tra2 and 9G8 are much stronger splicing activators than other SR protein family members and their activation potential is significantly higher than expected from their serine/arginine content. 9G8 activates splicing not only through its RS domains but also through its RNA-binding domain. The RS domains of Tra and Tra2 are required but not sufficient for efficient complex assembly. Thus, the regulated assembly of the dsx enhancer complexes leads to the generation of an extended activation domain to guarantee the ‘all or none’ splicing switch that is required during Drosophila sexual differentiation.