Miracle-dz/UniFAR-FTUs huggingface dataset:
How to know which food is good for you: bumblebees use taste to discriminate between different concentrations of food differing in nutrient content

ABSTRACT In view of the ongoing pollinator decline, the role of nutrition in bee health has received increasing attention. Bees obtain fat, carbohydrates and protein from pollen and nectar. As both excessive and deficient amounts of these macronutrients are detrimental, bees would benefit from assessing food quality to guarantee an optimal nutrient supply. While bees can detect sucrose and use it to assess nectar quality, it is unknown whether they can assess the macronutrient content of pollen. Previous studies have shown that bees preferentially collect pollen of higher protein content, suggesting that differences in pollen quality can be detected either by individual bees or via feedback from larvae. In this study, we examined whether and, if so, how individuals of the buff-tailed bumblebee (Bombus terrestris) discriminate between different concentrations of pollen and casein mixtures and thus nutrients. Bumblebees were trained using absolute and differential conditioning of the proboscis extension response (PER). As cues related to nutrient concentration could theoretically be perceived by either smell or taste, bees were tested on both olfactory and, for the first time, chemotactile perception. Using olfactory cues, bumblebees learned and discriminated between different pollen types and casein, but were unable to discriminate between different concentrations of these substances. However, when they touched the substances with their antennae, using chemotactile cues, they could also discriminate between different concentrations. Bumblebees are therefore able to discriminate between foods of different concentrations using contact chemosensory perception (taste). This ability may enable them to individually regulate the nutrient intake of their colonies. Highlighted Article: Bumblebee workers are able to discriminate different concentrations of a food mixture and hence nutrients by using their sense of taste, which may enable them to individually regulate food intake.
Volumetric HIFU Ablation guided by Multiplane MRI Thermometry

High Intensity Focused Ultrasound (HIFU) is commonly performed using an iterative point‐by‐point approach with the sonications interleaved by delays to allow for cool‐down of tissue. Although a safe sonication strategy, it remains rather slow due to the suboptimal utilization of deposited heat energy. As an alternative, we propose a volumetric ablation method where volumes larger than a focal spot are ablated per sonication by electronically steering the focal‐spot along multiple outwards‐moving concentric circles. A common problem of large volume ablations has been their safety with regards to nearfield heating. To this end, rapid multiplane thermometry is also introduced with coverage both parallel and perpendicular to the beam‐path. Our approach monitors the temperature rise during sonication at a temporal resolution comparable to that of heat‐development. Experiments were performed in an in vivo porcine model to assess the usefulness of the proposed volumetric sonication strategy and multiplane thermometry.
Norovirus vaccines: Correlates of protection, challenges and limitations

ABSTRACT Norovirus (NoV) is responsible for at least 50% of all gastroenteritis outbreaks worldwide. NoVs are classified into 6 different genogroups (GGI- GGVI) based on the viral capsid protein with NoV genogroup II genotype 4 (GII.4) being the predominant strain causing human diseases. Supportive therapy involving reversal of dehydration and electrolyte deficiency is the main treatment of NoV gastroenteritis. However, the worldwide increased recognition of NoV as an important agent of diarrheal gastroenteritis prompted researchers to focus on establishing preventive strategies conferring long-lasting immunity. This review describes the current status of animal and human vaccine models/studies targeting NoV and addresses the factors hampering the development of a broadly effective vaccine.
A technical demonstration of large-scale image object retrieval by efficient query evaluation and effective auxiliary visual feature discovery

In this demonstration, we present a real-time system that addresses three essential issues of large-scale image object retrieval: 1) image object retrieval-facilitating pseudo-objects in inverted indexing and novel object-level pseudo-relevance feedback for retrieval accuracy; 2) time efficiency-boosting the time efficiency and memory usage of object-level image retrieval by a novel inverted indexing structure and efficient query evaluation; 3) recall rate improvement--mining semantically relevant auxiliary visual features through visual and textual clusters in an unsupervised and scalable (i.e., MapReduce) manner. We are able to search over one-million image collection in respond to a user query in 121ms, with significantly better accuracy (+99%) than the traditional bag-of-words model.
Stable feature ranking with logistic regression ensembles

Beyond automated classification, supervised machine-learning models can be interpreted to find which features or combination of features distinguish sets of classes. Logistic Regression (LR) is an example of a model well-suited for human interpretation. Unfortunately, results from feature ranking with LR may not be reliable and reproducible for the same dataset. We demonstrate that stability and consistency can be achieved via ensembles (“LR ensembles”). As a specific example of the real-world utility of our associated framework, we apply LR ensembles to single-nucleotide polymorphisms (SNPs) associated with the recent speciation of the malaria vectors Anopheles gambiae and Anopheles coluzzii and compare with the more common univariate metric FST.
Teaching and learning programming and software engineering via interactive gaming

Massive Open Online Courses (MOOCs) have recently gained high popularity among various universities and even in global societies. A critical factor for their success in teaching and learning effectiveness is assignment grading. Traditional ways of assignment grading are not scalable and do not give timely or interactive feedback to students. To address these issues, we present an interactive-gaming-based teaching and learning platform called Pex4Fun. Pex4Fun is a browser-based teaching and learning environment targeting teachers and students for introductory to advanced programming or software engineering courses. At the core of the platform is an automated grading engine based on symbolic execution. In Pex4Fun, teachers can create virtual classrooms, customize existing courses, and publish new learning material including learning games. Pex4Fun was released to the public in June 2010 and since then the number of attempts made by users to solve games has reached over one million. Our work on Pex4Fun illustrates that a sophisticated software engineering technique-automated test generation-can be successfully used to underpin automatic grading in an online programming system that can scale to hundreds of thousands of users.
Brief report: Liddle's syndrome revisited--a disorder of sodium reabsorption in the distal tubule.

In 1963 Liddle et al.1 described a disorder that simulated primary aldosteronism, characterized by severe hypertension and hypokalemia but with negligible secretion of aldosterone. They theorized that this was “a disorder in which the renal tubules transport ions with such abnormal facility that the end result simulates that of a mineralocorticoid excess. ” We describe a woman with this syndrome (the index case1) in whom renal failure eventually developed and who received a cadaveric renal transplant at our institution in 1989. Her disorder resolved after transplantation, with normalization of the aldosterone and renin responses to salt restriction. The woman's extended .
Image denoising with unsupervised, information-theoretic, adaptive filtering

The problem of denoising images is one of the most important and widely studied prob­ lems in image processing and computer vision. Various image filtering strategies based on linear systems, statistics, information theory, and variational calculus, have been effec­ tive, but invariably make strong assumptions about the properties of the signal and/or noise. Therefore, they lack the generality to be easily applied to new applications or diverse image collections. This paper describes a novel unsupervised, information-theoretic, adaptive fil­ ter (UINTA) that improves the predictability of pixel intensities from their neighborhoods by decreasing the joint entropy between them. In this way UINTA automatically discov­ ers the statistical properties of the signal and can thereby reduce noise in a wide spectrum of images and applications. The paper describes the formulation required to minimize the joint entropy measure, presents several important practical considerations in estimating image-region statistics, and then presents a series of results and comparisons on both real and synthetic data. Image Denoising with Unsupervised, Information-Theoretic, Adaptive Filtering Suyash P. Awate and Ross T. Whitaker Scientific Computing and Imaging Institute, School of Computing, University of Utah
Mismatch interpretation by semantics-driven alignment ∗

This paper describes a method for the alignment of automatically recognized speech transcripts with formatted documents manually derived from the speech recognition results. Novel features of our alignment method are a parametrizable scoring function, an intelligent tokenization system drawing on domain knowledge, and semantic comparisons. The field of application are dictated medical reports processed by automatic speech recognition.
ANALYSIS AND SIMULATION OF A ROCKER-BOGIE EXPLORATION ROVER

Rovers will continue to play an important role in planetary exploration. Plans include the use of the rocker-bogie rover configuration. Here, models of the mechanics of this configuration are presented. Methods for solving the inverse kinematics of the system and quasi-static force analysis are described. Also described is a simulation based on the models of the rover’s performance. Experimental results confirm the validity of the models.
Evolution Analysis of Homogenous Source Code and its Application to Plagiarism Detection

Due to intelligent softwares and worldwide internet environment, unauthorized source code theft/copying and partial plagiarism is widespread. So the detecting the plagiarized source codes and software is getting important, especially in academic field. Though there have been announced lots of studies for detecting plagiarized pair of codes, we did not find somewhat more fundamental work for understanding the mechanism of plagiarism. So in order to improve the plagiarism detecting algorithm, it is desirable to reveal the whole procedure of code plagiarism. The basic idea of this paper is that software plagiarism can be considered as an evolution process of a source code. The final goal of our paper is to reconstruct the phylogenetic tree with a set of plagiarized codes. The main contribution of this paper is to propose an asymmetric code similarity measure, which enables us to guess the direction of plagiarism. For this purpose, we applied local alignment approach to detect a region of similar codes with a novel adaptive matching score matrix. To show the effectiveness and efficiency of our procedure, we conducted experiments on 20 artificially generated phylogenetic trees whose roots are selected from four program groups of ICPC (International Collegiate Programming Contest). Experiment showed that the proposed algorithm can effectively estimate the evolution direction, which enables us to identify plagiarized codes more accurately and reliably.
Oswestry Disability Index scoring made easy.

INTRODUCTION Low back pain effects up to 80% of the population at some time during their active life. Questionnaires are available to help measure pain and disability. The Oswestry Disability Index (ODI) is the most commonly used outcome measure for low back pain. The aim of this study was to see if training in completing the ODI forms improved the scoring accuracy. PATIENTS AND METHODS The last 100 ODI forms completed in a hospital's spinal clinic were reviewed retrospectively and errors in the scoring were identified. Staff members involved in scoring the questionnaire were made aware of the errors and the correct method of scoring explained. A chart was created with all possible scores to aid the staff with scoring. A prospective audit on 50 questionnaires was subsequently performed. RESULTS The retrospective study showed that 33 of the 100 forms had been incorrectly scored. All questionnaires where one or more sections were not completed by the patient were incorrectly scored. A scoring chart was developed and staff training was implemented. This reduced the error rate to 14% in the prospective audit. CONCLUSIONS Clinicians applying outcome measures should read the appropriate literature to ensure they understand the scoring system. Staff must then be given adequate training in the application of the questionnaires.
Novel Variable length Teager Energy Based features for person recognition from their hum

Most of the state-of-the-art voice biometrics systems use the natural speech signal (either read speech or spontaneous or contextual speech) from the subjects. In this paper, an attempt is made to identify speakers from their hum. A new feature set, viz., Variable length Teager Energy Based Mel Frequency Cepstral Coefficients (VTMFCC) is proposed for this problem. Experiments have been carried out for person identification and verification task using Linear Prediction Cepstral Coefficients (LPCC) and Mel Frequency Cepstral Coefficients (MFCC) with polynomial classifier of 2nd order approximation. It is shown that the speaker identification rate for proposed feature set outperforms LPCC by 13.6% and is competitive over baseline MFCC. For speaker verification, a reduction in equal error rate (EER) by 1.73% is achieved when a score-level fusion system is employed by combining evidence from MFCC and VTMFCC.
Serum amyloid A: high-density lipoproteins interaction and cardiovascular risk.

AIMS High-density lipoproteins (HDLs) are considered as anti-atherogenic. Recent experimental findings suggest that their biological properties can be modified in certain clinical conditions by accumulation of serum amyloid A (SAA). The effect of SAA on the association between HDL-cholesterol (HDL-C) and cardiovascular outcome remains unknown. METHODS AND RESULTS We examined the association of SAA and HDL-C with mortality in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study, which included 3310 patients undergoing coronary angiography. To validate our findings, we analysed 1255 participants of the German Diabetes and Dialysis study (4D) and 4027 participants of the Cooperative Health Research in the Region of Augsburg (KORA) S4 study. In LURIC, SAA concentrations predicted all-cause and cardiovascular mortality. In patients with low SAA, higher HDL-C was associated with lower all-cause and cardiovascular mortality. In contrast, in patients with high SAA, higher HDL-C was associated with increased all-cause and cardiovascular mortality, indicating that SAA indeed modifies the beneficial properties of HDL. We complemented these clinical observations by in vitro experiments, in which SAA impaired vascular functions of HDL. We further derived a formula for the simple calculation of the amount of biologically 'effective' HDL-C based on measured HDL-C and SAA from the LURIC study. In 4D and KORA S4 studies, we found that measured HDL-C was not associated with clinical outcomes, whereas calculated 'effective' HDL-C significantly predicted better outcome. CONCLUSION The acute-phase protein SAA modifies the biological effects of HDL-C in several clinical conditions. The concomitant measurement of SAA is a simple, useful, and clinically applicable surrogate for the vascular functionality of HDL.
Stability of NbCl5 and ZnMg Intercalated Graphite

NbCl5 and ZnMg intercalated graphite have been successfully synthesized by two-zone vapor transport method with the reactants sealed in the vacuum. The incorporation of NbCl5 and ZnMg results in randomly intercalation confirmed from the X-ray diffraction (XRD) analysis, and the doping effect change with the variation of intercalation time, the evolution of the doping is confirmed by X-ray photoelectron spectroscopy (XPS) and Raman analysis. The doped graphite is relatively stable at room temperature for up to 60 days from the Raman observations.
The Oral Thrombin Inhibitor Dabigatran: Strengths and Weaknesses

Abstract Since the quest for a better replacement of warfarin started several decades ago and new compounds were brought forward to clinical trials, the concept of an ideal anticoagulant frequently became presented in lectures and articles. We have here reviewed strengths and weaknesses of the oral thrombin inhibitor dabigatran in terms of pharmacokinetics and clinical data. When strengths clearly exceed the weaknesses for any characteristic, the drug fits into the concept of an ideal anticoagulant in that domain. It is evident that dabigatran does not accomplish that concept for all characteristics but it reaches well above warfarin. We believe it is unlikely that any drug will fulfill all criteria for the ideal anticoagulant. Laboratory testing for dabigatran will not be discussed in any detail in this article, which is instead the focus of other articles from this issue of Seminars in Thrombosis & Hemostasis.
Test Anxiety: A Major Educational Problem and What Can Be Done about It

There is growing evidence that motivation has a significant impact on school achievement (for a review of studies documenting this relationship, see Walberg & Uguroglu [1980]). Various lines of research, such as S. Sarason, Davidson, Lighthall, Waite, and Ruebush's (1960) work on anxiety in children, Atkinson and his colleagues' work on achievement motivation (Atkinson 1964, 1980; Atkinson & Feather 1966; Atkinson & Raynor 1974), Zigler's studies of motivation and testing (Zigler, Abelson, & Seitz 1973), Weiner's and Covington's research on achievement attributions (Weiner 1972, 1979; Coving-
Complexity Results for Quantified Boolean Formulae Based on Complete Propositional Languages

Several propositional fragments have been considered so far as target languages for knowledge compilation and used for improving computational tasks from major AI areas (like inference, diagnosis and planning); among them are the ordered binary decision diagrams, prime implicates, prime implicants, \formulae" in decomposable negation normal form. On the other hand, the validity problem val(QPROPP S) for Quantied Boolean Formulae (QBF) has been acknowledged for the past few years as an important issue for AI, and many solvers have been designed. In this paper, the complexity of restrictions of the validity problem for QBF obtained by imposing the matrix of the input QBF to belong to propositional fragments used as target languages for compilation, is identied. It turns out that this problem remains hard (PSPACE-complete) even under severe restrictions on the matrix of the input. Nevertheless some tractable restrictions are pointed out.
Intravascular (catheter) NMR receiver probe: Preliminary design analysis and application to canine iliofemoral imaging

This investigation explores the feasibility of a catheter‐based receiver probe for NMR study of arterial walls. Simulations and phantom experiments demonstrate the spatial response of several “inside‐out” probe coil designs, including loop, “birdcage,” “multipole,” “center return,” and opposed solenoids. For a target defined by an annulus in a plane perpendicular to B0, the opposed solenoid design provides substantially superior homogeneity to other designs considered. Canine iliofemoral artery images were acquired using a catheter probe in a whole‐body, 1.5‐T clinical imaging system. In situ (cadaver) images acquired with TE 70, TR 2400,2‐mm slice thickness, and 78 × 78‐μm in‐plane voxel size in 10‐min acquisition times show vessel wall structures identified as intima, internal elastic lamina, media, and adventitia. In vivo images from similar acquisition conditions are much more poorly resolved, presumably due to motion, despite the use of cardiac gating and gradient moment nulling, so the feasibility of obtaining high‐resolution in vivo MR images of the arterial wall remains in doubt. © 1992 Academic Press, Inc.
Emergence of Semantic Concepts in Visual Databases

Content-based image retrieval (CBIR) systems can be used also for other purposes than online access to unannotated image databases. In particular, when a CBIR system is equipped with an automatic image segmentation subsystem, keyword annotations given on image level can be focused on specific image segments. In this paper, we show that our PicSOM CBIR system is able to reveal semantic knowledge not only from keyword annotations but also from recorded online use of the system. This automatically extracted high abstraction level visual information can then be used to further improve the accuracy of the system and to categorize the objects of the database with semantic concepts. This process, we claim, then helps to bridge the semantic gap between low-level visual features available for computers and the high-level semantic terms used by the humans. The results of the experiments described in this paper support that view.
Mutual Enhancement of Schema Mapping and Data Mapping

Schema mapping and data mapping have been two topics widely studied in traditional database related communities. Recently, with the rising interest in the semantical web, the tasks of integrating heterogeneous information sources, both in a schema and a data instance level, are becoming of more practical importance. Current efforts at resolving these two mapping tasks have been carried out separately. In this paper, we propose a new method that simultaneously attacks these two tasks and achieves a kind of mutual enhancement between them. By applying our method to a movie-hunting scenario, we show that precision and recall are both quite high. Our method works well when dealing with numerical-valued attributes. We also show that this method is especially appealing from a semantic web perspective, given its assets of being relatively lightweight and easy to extend.
Unary negation

We study fragments of first-order logic and of least fixed point logic that allow only unary negation: negation of formulas with at most one free variable. These logics generalize many interesting known formalisms, including modal logic and the μcalculus, as well as conjunctive queries and monadic Datalog. We show that satisfiability and finite satisfiability are decidable for both fragments, and we pinpoint the complexity of satisfiability, finite satisfiability, and model checking. We also show that the unary negation fragment of first-order logic is model-theoretically very well behaved. In particular, it enjoys Craig Interpolation and the Projective Beth Property.