Miracle-dz/UniFAR-FTUs huggingface dataset:
Odorant receptor-mediated sperm activation in disease vector mosquitoes

Significance Mosquitoes use neuronal-expressed odorant receptors in their antennae to locate blood meal sources via chemical cues emitted by hosts. Although their expression in nonsensory tissues is known, the potential for odorant receptors to also mediate endogenous signaling events in insects has remained unexplored. In this study, we have identified a subset of odorant receptors showing transcript expression in the testes of the malaria mosquito, Anopheles gambiae. In addition, we provide functional evidence that the broadly conserved insect coreceptor, Orco, mediates flagellar activation in mosquito spermatozoa. These results are reminiscent of odorant receptor function in human sperm and may represent an intriguing example of convergent evolution. Insects, such as the malaria vector mosquito, Anopheles gambiae, depend upon chemoreceptors to respond to volatiles emitted from a range of environmental sources, most notably blood meal hosts and oviposition sites. A subset of peripheral signaling pathways involved in these insect chemosensory-dependent behaviors requires the activity of heteromeric odorant receptor (OR) ion channel complexes and ligands for numerous A. gambiae ORs (AgOrs) have been identified. Although AgOrs are expressed in nonhead appendages, studies characterizing potential AgOr function in nonolfactory tissues have not been conducted. In the present study, we explore the possibility that AgOrs mediate responses of spermatozoa to endogenous signaling molecules in A. gambiae. In addition to finding AgOr transcript expression in testes, we show that the OR coreceptor, AgOrco, is localized to the flagella of A. gambiae spermatozoa where Orco-specific agonists, antagonists, and other odorant ligands robustly activate flagella beating in an Orco-dependent process. We also demonstrate Orco expression and Orco-mediated activation of spermatozoa in the yellow fever mosquito, Aedes aegypti. Moreover, we find Orco localization in testes across distinct insect taxa and posit that OR-mediated responses in spermatozoa may represent a general characteristic of insect reproduction and an example of convergent evolution.
Affinity Propagation Clustering Using Path Based Similarity

Clustering is a fundamental task in data mining. Affinity propagation clustering (APC) is an effective and efficient clustering technique that has been applied in various domains. APC iteratively propagates information between affinity samples, updates the responsibility matrix and availability matrix, and employs these matrices to choose cluster centers (or exemplars) of respective clusters. However, since it mainly uses negative Euclidean distance between exemplars and samples as the similarity between them, it is difficult to identify clusters with complex structure. Therefore, the performance of APC deteriorates on samples distributed with complex structure. To mitigate this problem, we propose an improved APC based on a path-based similarity (APC-PS). APC-PS firstly utilizes negative Euclidean distance to find exemplars of clusters. Then, it employs the path-based similarity to measure the similarity between exemplars and samples, and to explore the underlying structure of clusters. Next, it assigns non-exemplar samples to their respective clusters via that similarity. Our empirical study on synthetic and UCI datasets shows that the proposed APC-PS significantly outperforms original APC and other related approaches.
A mono-objective evolutionary algorithm for Protein Structure Prediction in structural and energetic contexts

The Protein Structure Prediction (PSP) problem is concerned about the prediction of the native structure of a protein from its amino acid sequence. PSP is a challenging and computationally open problem. Therefore, several researches and methodologies have been developed for it. This paper presents the application of protpred-GROMACS, an evolutionary framework for PSP, in structural and energetic contexts. The performance of mono-objective algorithm was compared with other methodologies, such as multi-objective evolutionary algorithm, coarse grained monte carlo and replica exchange molecular dynamics.
The Bayesian New Statistics: Two historical trends converge

There have been two historical shifts in the practice of data analysis. One shift is from hypothesis testing to estimation with uncertainty and meta-analysis, which among frequentists in psychology has recently been dubbed “the New Statistics” (Cumming, 2014). A second shift is from frequentist methods to Bayesian methods. We explain and applaud both of these shifts. Our main goal in this article is to explain how Bayesian methods achieve the goals of the New Statistics better than frequentist methods. The two historical trends converge in Bayesian methods for estimation with uncertainty and meta-analysis.
A Model of Revision in Natural Language Generation

We outline a model of generation with revision, focusing on improving textual coherence. We argue that high quality text is more easily produced by iteratively revising and regenerating, as people do, rather than by using an architecturally more complex single pass generator. As a general area of study, the revision process presents interesting problems: Recognition of flaws in text requires a descriptive theory of what constitutes well written prose and a parser which can build a representation in those terms. Improving text requires associating flaws with strategies for improvement. The strategies, in turn, need to know what adjustments to the decisions made during the initial generation will produce appropriate modifications to the text. We compare our treatment of revision with those of Mann and Moore (1981), Gabriel (1984), and Mann (1983).
Bi-polynomial rank and determinantal complexity

The permanent vs. determinant problem is one of the most important problems in theoretical computer science, and is the main target of geometric complexity theory proposed by Mulmuley and Sohoni. The current best lower bound for the determinantal complexity of the d by d permanent polynomial is d^2/2, due to Mignon and Ressayre in 2004. Inspired by their proof method, we introduce a natural rank concept of polynomials, called the bi-polynomial rank. The bi-polynomial rank is related to width of an arithmetic branching program. The bi-polynomial rank of a homogeneous polynomial p of even degree 2k is defined as the minimum n such that p can be written as a summation of n products of polynomials of degree k. We prove that the bi-polynomial rank gives a lower bound of the determinantal complexity. As a consequence, the above Mignon and Ressayre bound is improved to (d-1)^2 + 1 over the field of reals. We show that the computation of the bi-polynomial rank is formulated as a rank minimization problem. Applying the concave minimization technique, we reduce the problem of lower-bounding determinantal complexity to that of proving the positive semidefiniteness of matrices, and this is a new approach for the permanent vs. determinant problem. We propose a computational approach for giving a lower bound of this rank minimization, via techniques of the concave minimization. This also yields a new strategy to attack the permanent vs. determinant problem.
A Novel Visualization System for Expressive Facial Motion Data Exploration

Facial emotions and expressive facial motions have become an intrinsic part of many graphics systems and human computer interaction applications. The dynamics and high dimensionality of facial motion data make its exploration and processing challenging. In this paper, we propose a novel visualization system for expressive facial motion data exploration. Based on Principal Component Analysis (PCA) dimensionality reduction on anatomical facial sub regions, high dimensional facial motion data is mapped to 3D spaces. We further rendered it as colored 3D trajectories and color represents different emotion. We design an intuitive interface to allow users effectively explore and analyze high dimensional facial motion spaces. The applications of our visualization system on novel facial motion synthesis and emotion recognition are demonstrated.
A novel way to statistically analyze morphologic changes in Dmp1-null osteocytes

Abstract Recent studies have revealed multiple roles of osteocytes in bone metabolism. However, detailed analyses of the embedded osteocytes in bone structure are still limited because of the high mineral content around these cells. In this study, we developed an innovative technique, the “FITC-Imaris technique”, which combines FITC ([2, 5]-Fluorescein isothiocyanate), confocal microscopy and Imaris software. With this method, we could not only visualize the 3-D morphology of embedded osteocytes, but more importantly, we were able to statistically quantitate the osteocyte structure in the cell surface area, total cell volume, and dendrite numbers. Furthermore, we made a side-by-side comparison of the new method with the acid-etched SEM imaging technique, a common imaging method for studies of osteocyte morphology with a much smaller cell depth (< 3 μm). Finally, we used the FITC-Imaris technique to show both the morphological and statistical differences in the osteocyte structure between the Dmp1-null mice (the osteomalacia model) and their age-matched control littermates. We expect that this newly developed technique will become a powerful tool to disclose more roles that osteocytes play in bone health and diseases.
Seeds of Illness, Seeds of Recovery: The Genesis of Suffering and the Role of Psychoanalysis

Ogden, Foreword. Seeds of Illness and the Role of Defences. The Culture of Reverie and the Culture of Evacuation. Container Inadequacy and Violent Emotions. Nachtraglichkeit and the Stork: The Analytic Field and Dream Thought Clinical Illustration. The Waking Dream and Narrations. 'Evidence': Starting Again from Bion. From the Tyranny of the Superego to the Democracy of Affects: The Transformational Passage Through the Analyst's Mind. Self-analysis and Gradients of Functioning in the Analyst. Pivotal-age Crises and Pivotal-event Crises. Psychoanalysis and Narration. Bibliography.
Tobacco control priorities for Arabic speakers: key findings from a baseline telephone survey of Arabic speakers residing in Sydney's south-west.

ISSUE ADDRESSED The Arabic-speaking population is a priority for tobacco control in Sydney's south-west. Current smoking prevalence and smokers' preferences for evidence-based cessation therapies are reported for this population. METHODS A telephone survey of Arabic speakers conducted in Sydney's south-west between August and November 2004 included: utilisation of tobacco products, tobacco and health knowledge, quit attempts and likelihood to use evidence-based cessation strategies. RESULTS A 70% response rate was achieved (n=1,102). Twenty-six per cent of respondents (95% CI 23.5-28.7) self-reported being current smokers. Logistic regression analysis demonstrated that poor knowledge of the harms of smoking (AOR=7.50, 95% CI 3.20-17.59), being male (AOR=2.63, 95% CI 1.89-3.65), being aged between 40 and 59 (AOR=1.44, 95% CI 1.06-1.96) and non-tertiary educated (AOR=1.44, 95% CI 1.06-1.97) were independent predictors of self-reported smoking. Smokers' preferences for evidence-based cessation strategies included: vouchers for discounted nicotine replacement therapy (NRT) (58.8%, 95% CI 52.9-64.6), standard self-help booklet (56.6%, 95% CI 50.7-62.4) and tailored self-help written materials (mailed) (54.0%, 95% CI 48.1- 59.9). More than one-third of all current cigarette smokers (39.4%, n=108, 95% CI 33.6-45.2) indicated they had made a quit attempt in the past 12 months. CONCLUSIONS Well-designed trials of efficacy for preferred evidence-based strategies, particularly among middle-aged male Arabic-speaking smokers, appear warranted prior to policy development and implementation.
The impact of common tumor necrosis factor haplotypes on the development of asthma in children: an Egyptian model.

Conflicting results have arisen among different ethnic populations with regard to the ability of tumor necrosis factor (TNF) to control the development of bronchial asthma. We examined common TNF polymorphisms (TNFA -1031C>T, TNFA -308G>A, and TNFB +252A>G) to develop a model of the associations between these genetic markers and the development of the disease in Egypt. Amplified DNA from buccal mucosa was genotyped for 240 children using polymerase chain reaction-restriction fragment length polymorphism. Skin prick test, total serum immunoglobulin E levels, and assessment of pulmonary functions were investigated. The onset age for one-third of the asthma patients in our study was between 7 and 10 years. The TNFA -1031C>T and TNFA -308G>A polymorphisms were strongly associated with the risk of asthma (p = 0.007, and p = 0.000, respectively), but the TNFB +252A>G polymorphism was not (p = 0.6). We detected a significant linkage between the +252A>G and -1031C>T, and another between the +252A>G and the -308G>A (p < 0.0001 for both). The -1031C>T and -308G>A polymorphisms were not linked (p = 0.14). The -308A/A genotype was absent, and the -308A allele was expressed only in patients with -308G/A heterozygosity (13%). All but the +252G/A genotype were also strongly associated with the severity of disease. Environmental factors, as genetic variations, clearly influence susceptibility, the onset, progression, and severity of bronchial asthma. More information is needed to develop genetic models of susceptibility for different ethnic populations.
Regulation and Return : The Role of Ambiguity

In this paper we examine the role of regulation of financial markets in an economy with both expected utility maximizing and ambiguity averse traders. Both types of traders are rational, but ambiguity averse traders do not have enough information about asset markets to form a prior over the set of possible models of return determination. Instead, they have a set of possible models of returns and their investment behavior is greatly affected by the most pessimistic model they consider. In particular, in the CARA-normal setting we examine their choice of whether or not to participate in the market is determined by the lowest mean return they believe to be possible, and when they do participate the amount of the asset they hold depends on the maximum variance of returns they consider possible. Because of these effects, regulations that affect these most pessimistic values can have surprisingly large effects on equilibrium asset prices. We show how the presence of ambiguity averse traders provides new rationale for deposit insurance, suitability rules, insider “short swing” trading profit restrictions and mutual fund restrictions.
Woodcock‐Johnson III: Test of Cognitive Abilities and Achievement

The Woodcock-Johnson III (Woodcock, McGrew, & Mather, 2001) consists of two conormed batteries: the WJ III Test of Cognitive Abilities (WJIII COG) and the WJ III Tests of Achievement (WJ III ACH). When used together, these batteries provide a comprehensive framework for evaluating and exploring the relationships and interactions among cognitive abilities and academic performance for individuals between the ages of 2 and 90+ years. The WJ III is based on the principle of selective testing; the examiner administers only the tests most relevant to the referral questions. Keywords: ability-achievement discrepancies; cognitive abilities; compuscore; learning disabilities
Selective Integration of Multiple Genomic Data for Biological Network Inference

In the field of computational biology, recently there has been a surge of interest in biological networks such as protein interaction networks, gene regulatory networks, or metabolic networks, which help us to understand the cellular machinery. Most of biological networks represent the relationships between genes or proteins. Namely the existence of edges means that the corresponding genes/proteins are related each other. In this paper, we are confronted with a problem to predict the interactions between genes/proteins. In our problem setting we are supposed to be given a part of the network and various genomic data such as gene expression data, localization data, and phylogenetic profile data. Our task is to predict the rest of the network. Yamanishi et al. [3] have already tackled the exactly same setting, and refer this problem to supervised network inference. Their approach uses canonical correlation analysis following the process of integration of multiple genomic data. The integration is done by linear combination of the multiple kernel matrices. We have developed another new method for this problem. Our method is based on information geometrical theory, and simultaneously infers the unknown subgraph and the weights of linear combination.
Delayed vs Undelayed Landmark Initialization for Bearing Only SLAM

The Simultaneous Localization And Mapping problem (SLAM) is one of the fundamental ones in mobile robotics. It concerns the incremental construction of an environment model from the fusion of sensory data (laser range finder, vision,. . . ) and proprioceptive data acquired by an inertial measurement unit or by odometry. Sensory data are processed to extract features (interest points, segments, planar patches. . . ) used as landmarks to locate the robot. A SLAM algorithm incrementally builds a Stochastic Map: at every data acquisition, it estimates the robot pose from the matchings between observed and previously perceived landmarks, and updates the map, fusing the matched informations and adding the new ones. The resulting model can be used by path-planning algorithms or other higher decisional layers. Using a sensor such that a video camera has many assets over the commonly used laser range finder with only horizontal scanning: a) Vision is a 3D sensor. Even for indoor robots for which pose can be represented in 2D [x, y, θ], 3D information is crucial; b) CCD cameras are of common use by now on embedded systems; they are cheap, light and small, power-saving and reliable; and c) Many algorithms are available from the vision community. They can be used to extract high level features from an image, and match them with previously perceived features included in the map using perceptual informations. Nevertheless, depth information cannot be retrieved using a single image. The classic Extended Kalman Filter (EKF) SLAM algorithm [8] cannot be directly applied as the landmark addition into the stochastic map requires a full gaussian estimation of its state. A special landmark initialization process must therefore be used which combines at least two observations of the same features from far enough robot poses. Moreover, whereas many authors make use of the Mahanalobis distance and the χ test to match observed landmarks with landmarks in the map, this method is not appropriate in the bearing-only case, as several candidates in the map can lay on the same optical ray in 3D space. This problem is known as Landmark Initialization in Bearing-Only SLAM. Bearing only SLAM using vision is very similar to the Structure From Motion (SFM) problem which is usually solved with Bundle Adjustment. The main difference is that robotic applications require an incremental and computationally tractable solution whereas SFM algorithm can run in a time consuming batch process. Links between non linear optimization algorithm for SFM and standard Kalman filter for bearing-only SLAM are studied in [6].
Morality, Self Knowledge and Human Suffering: An Essay on The Loss of Confidence in the World

1. Introduction 2. Thought Experiments, Justice, and Character 3. The Loss of Confidence in the World 4. The Real and the Imaginary in the Soldier's Experience 5. The Reality of Moral Features 6. Moral Principles and the Divided Conception of the Self 7 Self-Knowledge in the Light of a Dance 8. Conclusion: Toward Expressive Awareness
Current concepts and controversies in the management of early stage Hodgkin lymphoma

Over the past three decades, due to the recognition of late effects related to high-dose extended field radiotherapy and heavy alkylator chemotherapy, combined modality therapy with abbreviated chemotherapy and limited field radiotherapy has emerged as the standard of care for early stage Hodgkin lymphoma, with cure rates in excess of 80%. Currently, however, controversy remains over identifying the most appropriate criteria to risk-stratify patients with early stage disease, so that those with a favorable prognosis receive limited treatment without compromising cure rates and those with unfavorable risk receive more intensified therapy. The optimal risk stratification system remains unclear, with variable definitions of favorable and unfavorable disease used by research groups in North America and Europe. Thus, comparison of clinical trial results has been challenging, and additional controversies persist regarding optimal chemotherapy regimens, duration of therapy, and the role of radiotherapy. Investigations are ongoing to assess the potential of functional imaging and biomarkers as tools for risk stratification. The collective goal is to further refine current stratification strategies to allow for an individualized, risk-adapted treatment approach that minimizes long-term late effects without compromising high cure rates.
mEducator 3.0: Combining Semantic and Social Web Approaches in Sharing and Retrieving Medical Education Resources

Sharing of educational resources over the web has been a key development for both educators and learners in recent years. Pivotal roles in these developments have been played by following principles of the social/collaborative web, and more recently by exploiting advances in the semantic web front. In this paper an architecture that allows the sharing and retrieving of educational resources is proposed. In contrast to similar past attempts, this is now done without the need of copying or storing metadata in a centralised dataset/repository. Linked Data principles were used for exploring the metadata, while collaborative techniques were used in the systems that take advance of this architecture in order to enhance the end user experience, thereby offering a contemporary way to achieve resource adaptation and personalisation.
Impact of different types of tree nut, peanut, and soy nut consumption on serum C-reactive protein (CRP)

Background:The effects of different types of tree nut, peanut, and soy nut consumption on serum C - reactive protein (CRP) are not well established. we aimed to undertake a systematic review and meta-analysis of prospective studies to determine the effect of nut consumption (tree nuts, peanuts, and soy nuts) on serum CRP. Method:PubMed-Medline, Web of Science, Cochrane Database, and Google Scholar databases were searched (up until April 20 2016) to identify prospective studies evaluating the impact of tree nut, peanut, and soy nut consumption on serum CRP. Random effects models meta-analysis was used for quantitative data synthesis. Sensitivity analysis was conducted using the leave-one-out method. Heterogeneity was quantitatively assessed using the I2 index. Systematic review registration: CRD42016038044. Results:From a total of 844 entries identified via searches, 20 studies were included in the final selection. The meta-analysis indicated a nonsignificant increase in serum CRP concentrations following nut consumption (weighted mean difference [WMD] 0.17 mg/L, (95% CI –0.67 to 0.33, I2 52.1%). The WMDs for IL6 was –0.06(ng/dL), (95% CI –0.69 to 0.56, I2 9.6%), –0.71(mg/dL), (95% CI –1.11 to –0.30, I2 6.3%), for leptin, and -0.60(mg/dL), (95% CI –1.88 to 0.68, I2 5.6%) for adiponectin, and −0.18(mg/dL), (95% CI –1.24 to 0.88, I2 9.3%) for IL10 and –0.37 (pg/mL), (95% CI –0.90 to 0.16, I2 7.9%) for TNF-&agr;. These findings were robust in sensitivity analyses. Conclusions:This meta-analysis suggests that nut consumption significantly decrease leptin while have no significant effect on CRP, IL6, adiponectin, IL10, and TNF-&agr;.