Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-Time Quantitative PCR for Determining the Burden of Plasmodium falciparum Parasites during Pregnancy and Infancy

ABSTRACT Real-time quantitative PCR (RTQ-PCR) provides a quick, accurate, and reproducible quantification of parasites. However, the value of RTQ-PCR for predicting clinical outcomes of malaria is unknown. Here, we compared RTQ-PCR to microscopy of blood smears, nested PCR (nPCR), and parasite circulating-antigen (CAg) assays for detection of Plasmodium falciparum in pregnant Kenyan women and their infants and related these findings to parity and birth weights in their newborns (n = 554). nPCR was the most sensitive assay for detection of malaria in pregnancy, followed in decreasing order of sensitivity by RTQ-PCR, CAg assays, and blood smears. RTQ-PCR detected a higher frequency of malaria infection (46%) in maternal peripheral blood in primiparous than in multiparous women (35%; P < 0.001), with a >12-fold difference in parasite burden (geometric mean = 25,870 versus 2,143 amplicons/μl blood; P < 0.0001). Similarly, the presence of placental malaria determined by RTQ-PCR was approximately twofold higher in primiparous versus multiparous women (21% versus 13%; P < 0.01). The presence and intensity of malaria infection in pregnant women estimated by RTQ-PCR strongly correlated with low-birth-weight babies, especially in those with high amplicon numbers. RTQ-PCR identified malaria-infected women, missed by blood smear, who were at risk for having underweight offspring. By contrast, malaria detected by nPCR and CAg assay showed a much weaker association with parity or low birth weight. Thus, RTQ-PCR provides an estimate of parasite burden that is more sensitive than blood smear and is predictive of clinical outcomes of malaria infection in pregnant women and newborns.
Lessons from application of the UNRES force field to predictions of structures of CASP10 targets

Significance With the example of the coarse-grained United Residue model of polypeptide chains, this paper demonstrates that the physics-based approach for protein-structure prediction can lead to exceptionally good results when correct domain packing is an issue, even for a highly homologous target. The reason for this is probably that emphasis is placed on energetically favorable residue–residue interactions, including those with residues in relatively flexible linker regions; these regions are usually very different in the target compared with those of proteins in the databases used for template-based modeling. The results suggest that a combination of bioinformatics and a physics-based approach could result in a major increase in the prediction capacity of existing approaches. The performance of the physics-based protocol, whose main component is the United Residue (UNRES) physics-based coarse-grained force field, developed in our laboratory for the prediction of protein structure from amino acid sequence, is illustrated. Candidate models are selected, based on probabilities of the conformational families determined by multiplexed replica-exchange simulations, from the 10th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP10). For target T0663, classified as a new fold, which consists of two domains homologous to those of known proteins, UNRES predicted the correct symmetry of packing, in which the domains are rotated with respect to each other by 180° in the experimental structure. By contrast, models obtained by knowledge-based methods, in which each domain is modeled very accurately but not rotated, resulted in incorrect packing. Two UNRES models of this target were featured by the assessors. Correct domain packing was also predicted by UNRES for the homologous target T0644, which has a similar structure to that of T0663, except that the two domains are not rotated. Predictions for two other targets, T0668 and T0684_D2, are among the best ones by global distance test score. These results suggest that our physics-based method has substantial predictive power. In particular, it has the ability to predict domain–domain orientations, which is a significant advance in the state of the art.
The Validity of a Role-Played Measure of Student's Snack Selections.

Two measures of nutritious snack selection were compared in order to judge the validity of a role-played measure of snack selection. Elementary school students were provided a free-time snack period before and after nutrition education instruction. For half of these snack periods, students selected and ate snacks. For the remaining periods, food models (pictures) were provided, and students were asked to select those snacks they would like to eat, if real. A Pearson Product Moment correlation coefficient was calculated for snack and picture selections. None of these correlations was greater than . 48, and most did not reach statistical significance. It was concluded that the model snack procedure was not a valid measure of nutritious snack selection. It was suggested that explicit tests of validity may be important for other role-played and analogue measures of behavior.
Linked Open Data-enabled Strategies for Top-N Recommendations

The huge amount of interlinked information referring to different domains, provided by the Linked Open Data (LOD) initiative, could be e↵ectively exploited by recommender systems to deal with the cold-start and sparsity problems. In this paper we investigate the contribution of several features extracted from the Linked Open Data cloud to the accuracy of di↵erent recommendation algorithms. We focus on the top-N recommendation task in presence of binary user feedback and cold-start situations, that is, predicting ratings for users who have a few past ratings, and predicting ratings of items that have been rated by a few users. Results show the potential of Linked Open Data-enabled approaches to outperform existing state-of-the-art algorithms.
Analysis of Human Metabolic Core Using Hub-Based Centrality

Because detailed kinetic parameters are hardly available, topological analysis of inter-networks has proved to be greatly helpful to analyze genome-scale metabolic networks. Among lots of topological analysis approaches, centrality methods could be help to determine the most important nodes of a network and thus in helping to look for important metabolites in metabolic networks, as well as drug target and therapy design. In this paper, according to the standard hub-based centrality method, we studied the top 10 important metabolites in human metabolic network core with their biological and therapeutic signification.
A proposal of l1 regularized distance metric learning for high dimensional sparse vector space

In this paper, we focus on pattern recognition based on the vector space model with the high dimensional and sparse data. One of the pattern recognition methods is metric learning which learns a metric matrix by using the iterative optimization procedure. However most of the metric learning methods tend to cause overfitting and increasing computational time for high dimensional and sparse settings. To avoid these problems, we propose the method of l1 regularized metric learning by using the algorithm of alternating direction method of multiplier (ADMM) in the supervised setting. The effectiveness of our proposed method is clarified by classification experiments by using the Japanese newspaper article and UCI machine learning repository. And we show proposed method is the special case of the statistical sparse covariance selection.
The Role of the Auditory Brainstem in Processing Musically Relevant Pitch

Neuroimaging work has shed light on the cerebral architecture involved in processing the melodic and harmonic aspects of music. Here, recent evidence is reviewed illustrating that subcortical auditory structures contribute to the early formation and processing of musically relevant pitch. Electrophysiological recordings from the human brainstem and population responses from the auditory nerve reveal that nascent features of tonal music (e.g., consonance/dissonance, pitch salience, harmonic sonority) are evident at early, subcortical levels of the auditory pathway. The salience and harmonicity of brainstem activity is strongly correlated with listeners’ perceptual preferences and perceived consonance for the tonal relationships of music. Moreover, the hierarchical ordering of pitch intervals/chords described by the Western music practice and their perceptual consonance is well-predicted by the salience with which pitch combinations are encoded in subcortical auditory structures. While the neural correlates of consonance can be tuned and exaggerated with musical training, they persist even in the absence of musicianship or long-term enculturation. As such, it is posited that the structural foundations of musical pitch might result from innate processing performed by the central auditory system. A neurobiological predisposition for consonant, pleasant sounding pitch relationships may be one reason why these pitch combinations have been favored by composers and listeners for centuries. It is suggested that important perceptual dimensions of music emerge well before the auditory signal reaches cerebral cortex and prior to attentional engagement. While cortical mechanisms are no doubt critical to the perception, production, and enjoyment of music, the contribution of subcortical structures implicates a more integrated, hierarchically organized network underlying music processing within the brain.
Comparison and characterization of biosorption by Weissella viridescens MYU 205 of periodic group 12 metal ions.

Because heavy metals cause various health hazards, we studied biosorption by Weissella viridescens MYU 205. MYU 205 showed high biosorption for Cd (II) and Hg (II) and was low for Zn (II). The Hg (II) biosorption rate was high at about 80%. Different biosorptions were shown for each metal after successive incubation. About 20% of the Zn (II) biosorption was observed after 3 h. Cd (II) biosorption increased in a time-dependent manner until 3 h, then gradually decreased. Hg (II) was immediately sorbed at 79.6 ± 4.7% and decreased at 3 h to 52.9 ± 2.6%, and then gradually increased to 77.8 ± 3.6%. Using heat-killed cells, the rate of biosorption of Zn (II) and Cd (II) decreased whereas Hg (II) tended to increase. The metal resistance was high, that is Zn (II) > Cd (II) > Hg (II); while the affinity was opposite where MYU 205 showed high affinity to Hg (II) and low affinity to Zn (II). Our data shows lactic acid bacteria may be powerful heavy metal sorbents for detoxification.
The Path to Purpose: How Young People Find Their Calling in Life

Drawing on the revelatory results of a landmark study, William Damon -- one of the country's leading writers on the lives of young people, whose book Greater Expectations won the Parents' Choice Award -- brilliantly investigates the most pressing issue in the lives of youth today: why so many young people are "failing to launch" -- living at home longer, lacking career motivation, struggling to make a timely transition into adulthood, and not yet finding a life pursuit that inspires them. His groundbreaking study shows that about one-fifth of youth today are thriving -- highly engaged in activities they love and developing a clear sense of what they want to do with their lives -- but approximately one-fourth are still rudderless, at serious risk of never fulfilling their potential. The largest portion are teetering on the brink, in need of guidance to help them move forward: some are "dabblers" who pursue strings of disconnected interests with no real commitment; others, "dreamers" who have no realistic plans or understanding of what success will require. What makes the difference? Damon shows that the key ingredient for the highly engaged is that they have developed a clear sense of purpose in their lives that motivates them and gives them direction. Based on in-depth interviews, he takes readers inside the minds of the disengaged and drifting kids and exposes their confusion and anxiety about what they should do with their lives. He then offers compelling portraits of the young people who are thriving and identifies the nine key factors that have made the difference for them, presenting simple but powerful methods that parents and all adults can and must employ in order to cultivate that energized sense of purpose in young people that will launch them on the path to a deeply satisfying and productive life.
Exploring the stress-buffering effects of church-based and secular social support on self-rated health in late life.

OBJECTIVES The purpose of this study is to see if emotional support received from fellow church members and emotional support from secular social networks reduce the effects of financial strain on self-rated health. A second goal is to determine if church-based social support is a more important coping resource for older Blacks than for older Whites. METHODS The data come from the second wave of interviews with a nationwide sample of older people. Two groups of older adults are included in the analyses: Older Christians who go to church more than twice a year (N=548) and older people who do not go to church as frequently (N=238). RESULTS The data suggest that support from fellow church members tends to reduce the impact of financial strain on self-rated health, but support from secular network members fails to exert a similar effect. The findings also reveal that the stress-buffering effects of church-based support emerge among older Blacks, but not older Whites. DISCUSSION The findings from this study suggest that there may be something relatively unique about support that is provided by fellow church members.
Nonlinear Multi-Antenna Detection Methods

The paper investigates a nonlinear detection technique designed for multiple-antenna assisted receivers employed in space-division multiple-access systems. We derive the optimal solution of the nonlinear spatial processing assisted receiver for binary phase shift keying signalling, which we refer to as the Bayesian detector. It is shown that this optimal Bayesian receiver significantly outperforms the standard linear beamforming assisted receiver in terms of a reduced bit error rate, at the expense of an increased complexity, while the achievable system capacity is substantially enhanced with the advent of employing nonlinear detection. Specifically, when the spatial separation expressed in terms of the angle of arrival between the desired and interfering signals is below a certain threshold, a linear beamformer would fail to separate them, while a nonlinear detection assisted receiver is still capable of perform adequately. The adaptive implementation of the optimal Bayesian detector can be realized using a radial basis function network. Two techniques are presented for constructing block-data based adaptive nonlinear multiple-antenna assisted receivers. One of them is based on the relevance vector machine invoked for classification, while the other on the orthogonal forward selection procedure combined with the Fisher ratio class-separability measure. A recursive sample-by-sample adaptation procedure is also proposed for training nonlinear detectors based on an amalgam of enhanced $\kappa$-means clustering techniques and the recursive least squares algorithm.
Big science for growing minds : constructivist classrooms for young thinkers

Strong evidence from recent brain research shows that the intentional teaching of science is crucial in early childhood. Big Science for Growing Minds describes a groundbreaking curriculum that invites readers to rethink science education through a set of unifying concepts or big ideas. Using an integrated learning approach, the author shows teachers how to use readily available, low-cost items to create a safe classroom setting that fosters hands-on learning and exploration of real-life problems. The text includes classroom activities that connect science learning to mathematics, technology, art, and literacy.
A novel no-reference image quality assessment metric based on statistical independence

No-reference image quality assessment (NR IQA) has wide applicability to many problems. This paper focuses on the mechanism of divisive normalization transform (DNT) which simulates the behavior of visual cortex neurons to extract the independent components of natural images, analyzes the difference between the statistics of neighboring DNT coefficients of the images of a variety of distortion, and proposes a novel solution for NR IQA metric design. We demonstrate that measuring the statistical independence between neighboring DNT coefficients could provide features useful for quality assessment. The performance of the proposed method is quite satisfactory when it was tested on the popular LIVE, CSIQ and TID2008 databases. The experimental results are fairly competitive with the existing NR IQA metrics.
SApperloT Description of solver SApperloT submitted for the SAT-Race 2010

SApperloT is a hybrid solver that combines the idea of reference points with conflict-driven solving with clause learning (CDCL). Decision making with reference points (DMRP) was proposed by Goldberg [3, 4]. DMRP offers an appropriate method to analyse partial assignments during search: When the CDCL algorithm performs a restart the assignment stack is extended to a complete assignment R a so–called reference point that we choose to fulfill all binary clauses at first stage. This complete assignment is then taken as an initial reference point for the DMRP algorithm. In difference to state–of–the–art CDCL the DMRP approach bases its decisions on the set of clauses that is not satisfied by a current reference point. Even though DMRP requires some extra information for solving this can give a good direction for the search. More details can be found in [6].
Tumor necrosis factor alpha and phorbol 12‐myristate‐13‐acetate down‐regulate human 11β‐hydroxysteroid dehydrogenase type 2 through p50/p50 NF‐κB homodimers and Egr‐1

The 11β‐hydroxysteroid dehydrogenase type 2 (11β‐HSD2) regulates access of 11β‐hydroxyglucocorticoids to the mineralocorticoid receptor by reducing the hydroxyl group of these steroids at position 11. Previous cell culture studies revealed that tumor necrosis factor‐α (TNF‐α) down‐regulates 11β‐HSD2 activity. Here, we demonstrate that transgenic mice overexpressing TNF‐α have decreased mRNA abundance and activity of 11β‐HSD2 in kidney tissue, indicating that this effect may occur also in vivo. The analysis of the transcriptional regulation of 11β‐HSD2 by TNF‐α and phorbol 12‐myristate‐13‐acetate (PMA) with in vivo genomic footprinting in human colon SW620 cells revealed stimulus‐dependent protein‐DNA interactions in three promoter regions, κB1, Sp1/Egr‐1I, and Sp1/Egr‐1II. Chromatin immunoprecipitation and electrophoretic mobility shift assays demonstrated the relevance of NF‐κB binding to κB1 and of Egr‐1 binding to Sp1/Egr‐1 sites for the PMA and TNF‐α effect. We observed a temporal switch of binding to κB1 site from active p65/p50 heterodimers to inactive p50/p50 homodimers. TNF‐α or PMA treatment for 24 h resulted in accumulation of p50 and decrease of p65 nuclear proteins. Overexpression of p50 inhibited HSD11B2 promoter activity and overexpression of Egr‐1 inhibited transactivation of the HSD11B2 promoter by p65/p50. In conclusion, TNF‐α and PMA down‐regulate expression and activity of 11β‐HSD2 most likely by a coordinate binding of p50/p50 and Egr‐1 to the HSD11B2 promoter.
Obfuscated malware detection using API call dependency

Malwares pose a grave threat to security of a network and host systems. Many events such as Distributed Denial-of-Service attacks, spam emails etc., often have malwares as their root cause. So a great deal of research is being invested in detection and removal of malwares. Thus many malware detection systems or antivirus softwares have come up. But the drawback of these antivirus softwares is they rely upon signature matching approach for malware detection which can be easily defeated using simple code obfuscation techniques. This has given rise to a new generation of metamorphic and polymorphic malwares. In this paper we proposed the approach of monitoring interdependent system calls to detect obfuscated malicious programs. We took some sample malwares and some common obfuscation techniques. We tested these obfuscated malwares against open source antivirus ClamAV and our detection model. The results obtained have been elaborated further in the paper. Again how our algorithm is sound against many drawbacks of the API call monitoring approach such as API call reordering, garbage API call insertion etc., are also described.
How to Walk Your Dog in the Mountains with No Magic Leash

We describe a O(logn)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$O(\log n )$$\end{document}-approximation algorithm for computing the homotopic Fréchet distance between two polygonal curves that lie on the boundary of a triangulated topological disk. Prior to this work, algorithms were known only for curves on the Euclidean plane with polygonal obstacles. A key technical ingredient in our analysis is a O(logn)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$O(\log n)$$\end{document}-approximation algorithm for computing the minimum height of a homotopy between two curves. No algorithms were previously known for approximating this parameter. Surprisingly, it is not even known if computing either the homotopic Fréchet distance, or the minimum height of a homotopy, is in NP.
Characterisation of Culex quinquefasciatus (Diptera: Culicidae) larval habitats at ground level and temporal fluctuations of larval abundance in Córdoba, Argentina

The aims of this study were to characterise the ground-level larval habitats of the mosquito Culex quinquefasciatus, to determine the relationships between habitat characteristics and larval abundance and to examine seasonal larval-stage variations in Córdoba city. Every two weeks for two years, 15 larval habitats (natural and artificial water bodies, including shallow wells, drains, retention ponds, canals and ditches) were visited and sampled for larval mosquitoes. Data regarding the water depth, temperature and pH, permanence, the presence of aquatic vegetation and the density of collected mosquito larvae were recorded. Data on the average air temperatures and accumulated precipitation during the 15 days prior to each sampling date were also obtained. Cx. quinquefasciatus larvae were collected throughout the study period and were generally most abundant in the summer season. Generalised linear mixed models indicated the average air temperature and presence of dicotyledonous aquatic vegetation as variables that served as important predictors of larval densities. Additionally, permanent breeding sites supported high larval densities. In Córdoba city and possibly in other highly populated cities at the same latitude with the same environmental conditions, control programs should focus on permanent larval habitats with aquatic vegetation during the early spring, when the Cx. quinquefasciatus population begins to increase.