Miracle-dz/UniFAR-FTUs huggingface dataset:
Drosophila Fragile X Mental Retardation Protein and Metabotropic Glutamate Receptor A Convergently Regulate the Synaptic Ratio of Ionotropic Glutamate Receptor Subclasses

A current hypothesis proposes that fragile X mental retardation protein (FMRP), an RNA-binding translational regulator, acts downstream of glutamatergic transmission, via metabotropic glutamate receptor (mGluR) Gq-dependent signaling, to modulate protein synthesis critical for trafficking ionotropic glutamate receptors (iGluRs) at synapses. However, direct evidence linking FMRP and mGluR function with iGluR synaptic expression is limited. In this study, we use the Drosophila fragile X model to test this hypothesis at the well characterized glutamatergic neuromuscular junction (NMJ). Two iGluR classes reside at this synapse, each containing common GluRIIC (III), IID and IIE subunits, and variable GluRIIA (A-class) or GluRIIB (B-class) subunits. In Drosophila fragile X mental retardation 1 (dfmr1) null mutants, A-class GluRs accumulate and B-class GluRs are lost, whereas total GluR levels do not change, resulting in a striking change in GluR subclass ratio at individual synapses. The sole Drosophila mGluR, DmGluRA, is also expressed at the NMJ. In dmGluRA null mutants, both iGluR classes increase, resulting in an increase in total synaptic GluR content at individual synapses. Targeted postsynaptic dmGluRA overexpression causes the exact opposite GluR phenotype to the dfmr1 null, confirming postsynaptic GluR subtype-specific regulation. In dfmr1; dmGluRA double null mutants, there is an additive increase in A-class GluRs, and a similar additive impact on B-class GluRs, toward normal levels in the double mutants. These results show that both dFMRP and DmGluRA differentially regulate the abundance of different GluR subclasses in a convergent mechanism within individual postsynaptic domains.
Nonlinear Optical Imaging of Cellular Processes in Breast Cancer

Abstract Nonlinear optical imaging techniques such as multiphoton and second harmonic generation (SHG) microscopy used in conjunction with novel signal analysis techniques such as spectroscopic and fluorescence excited state lifetime detection have begun to be used widely for biological studies. This is largely due to their promise to noninvasively monitor the intracellular processes of a cell together with the cell's interaction with its microenvironment. Compared to other optical methods these modalities provide superior depth penetration and viability and have the additional advantage in that they are compatible technologies that can be applied simultaneously. Therefore, application of these nonlinear optical approaches to the study of breast cancer holds particular promise as these techniques can be used to image exogeneous fluorophores such as green fluorescent protein as well as intrinsic signals such as SHG from collagen and endogenous fluorescence from nicotinamide adenine dinucleotide or flavin adenine dinucleotide. In this article the application of multiphoton excitation, SHG, and fluorescence lifetime imaging microscopy to relevant issues regarding the tumor-stromal interaction, cellular metabolism, and cell signaling in breast cancer is described. Furthermore, the ability to record and monitor the intrinsic fluorescence and SHG signals provides a unique tool for researchers to understand key events in cancer progression in its natural context.
Scientific Concepts and Reflection

An interpretation of the idea of "scientific concepts" as the products of science that should supersede prior everyday knowledge of pupils is untenable and obscures the relation between learning, reflection, and morality. Instead, in this article I propose to think of scientific (or "scholarly") concepts as the products of reflection in a practice that includes choices about the future development of that praxis and are, in that sense, of a moral nature. Teaching scholarly concepts should be "genetically adequate," meaning that it should encourage pupils to reflect and interpret concepts as elements to be used in co-reconstruction of practices. In teaching, subject matter, identity formation, and the development of practices are interconnected.
Computing Highly Correlated Positions Using Mutual Information and Graph Theory for G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are a superfamily of seven transmembrane-spanning proteins involved in a wide array of physiological functions and are the most common targets of pharmaceuticals. This study aims to identify a cohort or clique of positions that share high mutual information. Using a multiple sequence alignment of the transmembrane (TM) domains, we calculated the mutual information between all inter-TM pairs of aligned positions and ranked the pairs by mutual information. A mutual information graph was constructed with vertices that corresponded to TM positions and edges between vertices were drawn if the mutual information exceeded a threshold of statistical significance. Positions with high degree (i.e. had significant mutual information with a large number of other positions) were found to line a well defined inter-TM ligand binding cavity for class A as well as class C GPCRs. Although the natural ligands of class C receptors bind to their extracellular N-terminal domains, the possibility of modulating their activity through ligands that bind to their helical bundle has been reported. Such positions were not found for class B GPCRs, in agreement with the observation that there are not known ligands that bind within their TM helical bundle. All identified key positions formed a clique within the MI graph of interest. For a subset of class A receptors we also considered the alignment of a portion of the second extracellular loop, and found that the two positions adjacent to the conserved Cys that bridges the loop with the TM3 qualified as key positions. Our algorithm may be useful for localizing topologically conserved regions in other protein families.
Registration of retinal images using blood vessel features

The registration of retinal images has significant importance in the operations of additional diagnosis and to determine the ailment progression of various retinal diseases. This paper deals with a feature based technique for retinal image registration. The purpose of the proposed method is to assist ophthalmologist to remark variations that happen in the blood vessel structure because of different pathological abnormalities. The retinal image comprises of various aspects such as optic disc(OD), blood vessels(BV), macula, fovea etc. In our approach blood vessels are taken as main feature as blood vessels can be considered as an important benchmark for disorders viz. diabetes, age related macular edema and retinopathy of prematurity (ROP). The segmentation of blood vessels is done by using morphological operation. For the registration section, the OD is segmented from which the OD center is calculated. The center of the OD is considered as control point and it is used to correct the orientation difference between the two images to be registered. By minimizing the rotational and translational differences between them, the registration is achieved.
Covariance tracking algorithm based on particle filter and adaptive template update

The region descriptor and template update strategy are the keys of object tracking algorithm. In the paper, we proposed an adaptive template update method based on region covariance descriptor to track the object in a complex circumstance using particle filter. We experimented the proposed approach on people in video sequences, and experimental results show that this method has better performance.
Multi-satellite observation integrated scheduling method oriented to emergency tasks and common tasks

Satellite observation scheduling plays a significant role in improving the efficiency of satellite observation systems. Al- though many scheduling algorithms have been proposed, emer- gency tasks, characterized as importance and urgency (e.g., ob- servation tasks orienting to the earthquake area and military con- flict area), have not been taken into account yet. Therefore, it is crucial to investigate the satellite integrated scheduling methods, which focus on meeting the requirements of emergency tasks while maximizing the profit of common tasks. Firstly, a pretreatment ap- proach is proposed, which eliminates conflicts among emergency tasks and allocates all tasks with a potential time-window to related orbits of satellites. Secondly, a mathematical model and an acyclic directed graph model are constructed. Thirdly, a hybrid ant colony optimization method mixed with iteration local search (ACO-ILS) is established to solve the problem. Moreover, to guarantee all solutions satisfying the emergency task requirement constraints, a constraint repair method is presented. Extensive experimental simulations show that the proposed integrated scheduling method is superior to two-phased scheduling methods, the performance of ACO-ILS is greatly improved in both evolution speed and solution quality by iteration local search, and ACO-ILS outperforms both genetic algorithm and simulated annealing algorithm.
Human mobility patterns in different communities: a mobile phone data-based social network approach

Detecting intensely connected sub-networks, or communities, from social networks has attracted much attention in social network studies. The widespread use of location-awareness devices provides a novel data source for constructing spatially embedded networks and uncovering spatial features of different population groups. Using an empirical mobile phone data-set, this paper attempts to explore the spatial distributions and human mobility patterns, as well as the interrelationship between them, at the community level. Three spatial patterns of communities are identified with the community detection algorithm and kernel density map method: single-centred distribution, dual-centred distribution and zonal distribution. We find different movement characteristics of these three community types by analysing angle distribution of trajectories and radius of gyration of users. Furthermore, we analyse spatial and temporal travel patterns for the users in dual-centred communities. The results indicate that people’s commuting travel brings about spatial interaction between urban district and suburbs, and verify our hypothesis that the distance decay effect along with social phenomena such as the home–work separation contributes to the formation of different community distributions.
Informed separation of spatial images of stereo music recordings using second-order statistics

In this work we address a reverse audio engineering problem, i.e. the separation of stereo tracks of professionally produced music recordings. More precisely, we apply a spatial filtering approach with a quadratic constraint using an explicit source-image-mixture model. The model parameters are “learned” from a given set of original stereo tracks, reduced in size and used afterwards to demix the desired tracks in best possible quality from a preexisting mixture. Our approach implicates a side-information rate of 10 kbps per source or channel and has a low computational complexity. The results obtained for the SiSEC 2013 dataset are intended to be used as reference for comparison with unpublished approaches.
Sentiment Polarity Classification at EVALITA: Lessons Learned and Open Challenges

Sentiment analysis in social media is a popular task attracting the interest of the research community, also in recent evaluation campaigns of natural language processing tasks in several languages. We report on our experience in the organization of SENTIment POLarity Classification Task (SENTIPOLC), a shared task on sentiment classification of Italian tweets, proposed for the first time in 2014 within the Evalita evaluation campaign. We present the datasets—which include an enriched annotation scheme for dealing with the impact of figurative language on polarity—the evaluation methodology, and discuss the approaches and results of participating systems. We also offer a reflection on the open challenges of state-of-the-art systems for sentiment analysis of microblogging in Italian, as they emerge from a qualitative analysis of misclassified tweets. Finally, we provide an evaluation of the resources we have created, and share the lessons learned by running this task for two consecutive editions.
(Dis)entangling medicine and media: a qualitative analysis of the relationship between the fields of healthcare and journalism

ABSTRACT Previous research has illustrated that journalists play an active role in the production of health news. The current study explores the relationship between the fields of healthcare and journalism from a healthcare perspective. Drawing on Bourdieu’s theory of fields and Gieryn’s concept of boundary-work, this study employed elite interviewing to analyse how the relations between these two fields were reflected and negotiated in the discourses of Belgian health-policy stakeholders. Our analysis illustrated that health-policy stakeholders perceived medicine and the news media as two different cultures and, therefore, discursively positioned news media actors as outsiders. Additionally, we showed that the nature of the relationship between health-policy stakeholders and the news media was linked to health-policy stakeholders’ position within the healthcare field. Through this analysis, we illustrate the value of using the concept of boundary-work as an analytical instrument to study the relationships between fields.
Estimating the $K$ function of a point process with an application to cosmology

Motivated by the study of an important data set for understanding the large-scale structure of the universe, this work considers the estimation of the reduced second-moment function, or K function, of a stationary point process on R observed over a large number of segments of possibly varying lengths. Theory and simulation are used to compare the behavior of isotropic and rigid motion correction estimators and some modifications of these estimators. These results generally support the use of modified versions of the rigid motion correction. When applied to a catalog of astronomical objects known as absorbers, the proposed methods confirm results from earlier analyses of the absorber catalog showing clear evidence of clustering up to 50 h -1 Mpc and marginal evidence for clustering of matter on spatial scales beyond 100 h -1 Mpc, which is beyond the distance at which clustering of matter is now generally accepted to exist.
Carer Factors Associated with Foster-Placement Success and Breakdown

The characteristics of carers in successful foster placements are identified to enable targeting them through customised marketing and recruitment campaigns. A longitudinal study with seventy-five carers was conducted over twenty months. Eleven instances of placement breakdown were compared to placements that did not break down. Several personal and family factors were identified as increasing the likelihood of foster-placement success, including higher cognitive empathy of the carer, a high level of social support from family, a high-quality carer-partner relationship, higher levels of care-giving and role-carer demand satisfaction, and a good match, fewer conflicts and better relationship between the carer and foster child. Conflicts between the carer and the child mediate the association between carer-partner relationship quality and carer satisfaction with role demands. Findings have important practical implications: additional evaluations should be conducted during screening processes with a focus on the key markers of placement success identified in this study; more emphasis should be placed on developing support networks amongst carers' friends and family; and greater involvement of carer partners in screening and training processes is of key importance.
Google+ or Google-?: dissecting the evolution of the new OSN in its first year

In the era when Facebook and Twitter dominate the market for social media, Google has introduced Google+ (G+) and reported a significant growth in its size while others called it a ghost town. This begs the question that "whether G+ can really attract a significant number of connected and active users despite the dominance of Facebook and Twitter? ". This paper tackles the above question by presenting a detailed characterization of G+ based on large scale measurements. We identify the main components of G+ structure, characterize the key features of their users and their evolution over time. We then conduct detailed analysis on the evolution of connectivity and activity among users in the largest connected component (LCC) of G+ structure, and compare their characteristics with other major OSNs. We show that despite the dramatic growth in the size of G+, the relative size of LCC has been decreasing and its connectivity has become less clustered. While the aggregate user activity has gradually increased, only a very small fraction of users exhibit any type of activity. To our knowledge, our study offers the most comprehensive characterization of G+ based on the largest collected data sets.
Fat, meat, and prostate cancer.

Although the 25 years of epidemiologic studies have reported on the relation of dietary fat to the risk of prostate cancer the role of dietary fat in prostate cancer remains unclear. It is noted that the hypothesis that dietary fat increases the risk of prostate cancer grew out of early ecologic studies that showed a positive correlation between prostate cancer mortality and per capita intake of fat meat and milk in international comparisons. In this presentation of epidemiologic studies fat and meat are both considered because most research has been done in western populations where meat is an important contributor to total and saturated fat intake. However it is emphasized in the discussion that other constituents of meat could also contribute to a carcinogenic effect. Overall the findings from case-control studies are distinguished from those of cohort studies and statistically significant risk ratios are noted. All findings are risk ratios above 1.3 and include the results from 3 cohort analyses. Several research needs are identified.
Random movement strategies in self-exploration for a humanoid robot

Motor Babbling has been identified as a self-exploring behaviour adopted by infants and is fundamental for the development of more complex behaviours, self-awareness and social interaction skills. Here, we adopt this paradigm for the learning strategies of a humanoid robot that maps its random arm movements with its head movements, determined by the perception of its own body. Finally, we analyse three random movement strategies and experimentally test on a humanoid robot how they affect the learning speed.
KINEMATIC PREDICTION FOR INTERCEPT USING A NEURAL KALMAN FILTER

Abstract The neural extended Kalman filter is a technique that learns unmodelled dynamics while performing state estimation. This coupled system performs the state estimation of the plant while estimating a function approximation of the difference between the system model and the dynamics of the true plant. At each sample step, this approximation is added to the existing model improving the state estimate. This neural estimator is applied to a two-dimensional intercept problem as a target tracker providing the control reference signal. Comparisons between different prediction times used in the control are provided for both the neural tracker and a baseline tracker.
Don't stand so close to me: Users' attitudinal and behavioral responses to personal space invasion by robots

When around humans, one might expect that a social robot would act according to the social norms people expect of each other. When someone does not adhere to a prevalent social norm, people usually feel threatened and uncomfortable. In comparison, insight is needed into what is perceived as socially normative behavior for robots. We conducted an experiment in which a robot approached a participant in order to determine the effect of personal space invasion. We manipulated the agent-type (human/robot) and the approach speed (slow/fast) of the agent towards the participant. Unexpectedly, our results show that the participants displayed more compensatory behavior toward the robot than toward the human confederate. Interestingly, we found that participants tended to trust the faster robot more compared and the faster human less. We consider these responses toward personal space invasion as an indication that people react differently to robots as they do to humans, and with more intensity.
Calibration of a robot-based measuring system

A robot-based measuring system is presented for object digitalization. In order to ensure the precision of the scanning system, a novel calibration scheme called as one-stage approach is proposed. This procedure mainly utilizes a chess board as calibration target and calibrates the range finder and hand-eye model simultaneously using the same reference points to eliminate the influences of the range finder calibration error on the hand-eye calibration. Finally, some experimental results are reported and analyzed.
Creating Corpora for Computational Research in Arab-Andalusian Music

Research corpora are fundamental for the computational study of music. The design criteria with which to create them is a research task in itself. These corpora need to be well suited for the specific research problems to be addressed. Since these research problems are also shaped by musical, cultural and other specific aspects of the music traditions to be studied, the research corpora should take these specificities into account. In this paper we address the problems of creating corpora for computational research on Arab-Andalusian music, considering several relevant criteria for creating such corpora. We focus on the problems raised during the annotation process of the corpora, specifically the language issues surrounding this art music tradition. Following the criteria, we created a research corpus consisting of audio recordings with their corresponding metadata, lyrics and music scores. So far we have gathered 338 recordings from 3 different Arab-Andalusian music schools of Morocco, covering most of the musical modes, rhythms and forms of this art music tradition. The Arab-Andalusian corpus is accessible to the research community from a central online repository. Moreover, the audio recordings of this corpora are freely available through the Internet Archive repository. The Arab-Andalusian corpus can be used to generate test datasets, which can be used as ground truth to test several computational research tasks.
Joint Analysis of Static and Dynamic Importance in the Eye-Tracking Records of Web Page Readers

Heat maps highlight cumulative, static importance in eye-tracking records, while network analysis helps to elucidate dynamic importance from transitional relations. The present study was designed to perform both analyses in the same conceptual framework, i.e., network representation. For this purpose, heat maps comprising 5 × 5 segments were overlaid with networks, both of which were produced from the eye-tracking records of 20 subjects who read 10 top web pages that were classified into three layout types. The heat of the segments was graded on the basis of five percentile scores, whereas the core-peripheral nodes were identified by the agreement of centrality and ranking indices. The congruence between the two types of importance was generally good at the node level and the community levels. Additional findings included a) mixed patterns of the sustained fixations (i.e., loops) within the total fixations, and b) an increase in reciprocity as the network scope was narrowed to communities and then to the core neighborhoods.