Miracle-dz/UniFAR-FTUs huggingface dataset:
FRAXE-associated mental retardation protein (FMR2) is an RNA-binding protein with high affinity for G-quartet RNA forming structure

FRAXE is a form of mild to moderate mental retardation due to the silencing of the FMR2 gene. The cellular function of FMR2 protein is presently unknown. By analogy with its homologue AF4, FMR2 was supposed to have a role in transcriptional regulation, but robust evidences supporting this hypothesis are lacking. We observed that FMR2 co-localizes with the splicing factor SC35 in nuclear speckles, the nuclear regions where splicing factors are concentrated, assembled and modified. Similarly to what was reported for splicing factors, blocking splicing or transcription leads to the accumulation of FMR2 in enlarged, rounded speckles. FMR2 is also localized in the nucleolus when splicing is blocked. We show here that FMR2 is able to specifically bind the G-quartet-forming RNA structure with high affinity. Remarkably, in vivo, in the presence of FMR2, the ESE action of the G-quartet situated in mRNA of an alternatively spliced exon of a minigene or of the putative target FMR1 appears reduced. Interestingly, FMR1 is silenced in the fragile X syndrome, another form of mental retardation. All together, our findings strongly suggest that FMR2 is an RNA-binding protein, which might be involved in alternative splicing regulation through an interaction with G-quartet RNA structure.
Factors concerning access to a potential drug consumption room in Dublin, Ireland

Abstract Drug consumption rooms (DCRs) are a harm reduction service used by more than ten countries worldwide as a means of addressing localised problem drug use. Ireland is now in the process of introducing a DCR. Internationally, each DCR has its own rules and regulations addressing access, which are suited to the local drug using community. A qualitative exploratory case study design was implemented during 2016 with the aim of determining approaches to access for a DCR with input from participants working inside and outside drug services. Nineteen participants were interviewed in depth including service users and staff from a large city centre drug service, and key informants with experience working in drug policy within the Ministry of Health. The interview guide addressed their experiences and knowledge of problem drug use in Dublin, alongside their opinion of the viability of established DCR rules for a Dublin location. Participants were supportive of a Dublin-based service, and in general concurred with the existing rules of other DCRs. However, there were concerns about how a DCR and health and drug services in Dublin would coordinate. Other key issues that emerged here were problems surrounding drug using parents, addressing the public approach to problem drug use, and support for staff working in services. This study also highlighted the difference in opinion between stakeholder groups, and the implications this will have on the development and implementation of a service.
Automatic extraction of semantic content from medical discharge records

Semi-structured medical texts like discharge summaries are rich sources of information that can exploit the research results of physicians by performing statistical analysis of similar cases. In this paper we introduce a system based on Machine Learning algorithms that successfully classifies discharge records according to the smoking status of the patient (we distinguish between current smoker, past smoker, smoker /where a decision between the former two classes cannot be made/, non-smoker and unknown /where the document contains no data on smoking status/ classes). Such systems are useful for examining the connection between certain social habits and diseases like cancer or asthma. We trained and tested our model on the shared task organized by the I2B2 (Informatics for Integrating Biology and the Bedside) research center [1], and despite the low amount of training data available, our system shows promising results in identifying the smoking habits of patients based on their medical discharge summaries.
Localization of actin in Dictyostelium amebas by immunofluorescence

Antibody prepared against avian smooth muscle actin has been used to localize actin in the slime mold, Dictyostelium discoideum. The distribution of actin in migrating cells is different from that in feeding cells. Migrating amebas display fluorescence primarily in advancing regions whereas feeding amebas show uniform fluorescence throughout. The reaction is specific for actin since the fluorescence observed is blocked when the antibody is absorbed by actin purified from avian skeletal muscle, human platelets, and Dictyostelium. These results, in addition to describing the distribution of actin in D. discoideum, demonstrate that actins from these diverse sources share at least one common antigenic determinant.
Regular Sparse Crossbar Concentrators

A bipartite concentrator is a single stage sparse crossbar switching device that can connect any m of its n/spl ges/m inputs to its m outputs, possibly without the ability to distinguish their order. Fat-and-slim crossbars were introduced recently to show that bipartite concentrators can be constructed with a minimum number of crosspoints for any number of inputs and outputs. We generalize these graphs to obtain bipartite concentrators with nearly a fixed fanout without altering their (n-m+1)m crosspoint complexity. We also present an O(log n)-time algorithm to route arbitrary concentration assignments on this new family of fat-and-slim crossbars.
Bayesian bpproach based decision in speaker verification

Considering Bayesian decision framework applied in the context of speaker verification, this paper presents a new way of handling troublesome anti-speaker model by proposing a redefinition of hypotheses involved in the classical statistical hypothesis test. This new definition of hypotheses is then implemented through a speaker independent normalization technique, named MAP approach. Besides supporting these new hypotheses, MAP approach takes the advantages of projecting likelihood scores into a probabilistic domain and therefore of providing the decision threshold with bounded and meaningful values. In this paper, different variants of MAP approach are presented which mainly aims at reducing likelihood variability, well-known in speaker verification to degrade system performance. MAP approach is firstly combined with classical normalization techniques (likelihood ratio normalization (world model) and/or Hnorm normalization technique). The second kind of variants consists in redesigning MAP approach to become speaker dependent. Experiments conducted on a subset of Switchboard database involving these different variants have showed that MAP approach is able to perform as well as classical normalization techniques while yielding probabilistic scores suitable for the decision threshold setting or the fusion of recognizer scores in the context of a multi-recognizer architecture.
Research of Complexity in Cellular Automata through Evolutionary Algorithms

This paper presents an evolutionary approach of the search of cellular automata accepting gliders. The proposed technique is based on a specific fitness function taking in account the spatial evolution, the number of living cells as well as the presence of gliders. The results show that the genetic algorithmic is a promising tool for the search of cellular automata with specific behaviours, and then could prove to be decisive for identification of new automata supporting universal computation.
Ad hoc mobile multicast routing using the concept of long-lived routes

Mobile ad hoc networks are recognized by their abilities to form, sustain, and deform networks on-the-fly without the need for any pre-established and fixed infrastructures. This wireless multi-hop technology requires adaptive networking protocols with low control overhead and low power consumption to operate efficiently. Existing research so far are mainly concerned with unicast routing for ad hoc mobile networks. There is a growing interest in supporting multicast communication in an ad hoc mobile environment. In this paper, the associativity-based ad hoc multicast (ABAM) routing protocol is proposed. The concept of association stability is utilized during multicast tree discovery, selection, and reconfiguration. This allows routes that are long-lived to be selected, thereby reducing the frequency of route reconstructions. ABAM employs a localized route reconstruction strategy in response to migrations by source, receiver, and tree nodes. It can repair an affected subtree via a single route reconstruction operation. ABAM is robust since the repair can be triggered by a node in the tree or by the migrated node itself. ABAM is also capable of handling multicast group dynamics when mobile hosts decide to join and leave an existing multicast group. Our simulation results reveal that under different mobility scenarios and multicast group size, ABAM has low communication overhead and yields better throughput performance. Copyright © 2001 John Wiley & Sons, Ltd.
Performance and Power Estimation for Mobile-Cloud Applications on Virtualized Platforms

Performance optimization and energy-saving have become major challenges for both hardware designers and software developers of mobile systems due to limited battery capacities. Analysis of the performance and power consumption in such a system and employment of energy-saving techniques as early as possible are keys to competitive products designs. With virtual platforms powered by simulation/emulation engines to help hardware designers in the early design stages for verifying the functional correctness of a hardware design or testing software applications before the hardware is ready, we propose a framework to further support hardware/software co-design with advanced performance and power analysis facilities. Our case studies and experimental results show that our framework can reflect the performance and power behavior of mobile-cloud applications and help hardware/software designers in reducing the energy consumption on these systems.
Multiple kernel boosting based tracking using pooling features

We present a novel Multiple Kernel Boosting (MKB) based tracking method using pooling features. Pooling features are a type of features generated by pooling methods, which are more distinctive and significant than low level features. In the pooling step, we not only use average pooling and spatial pyramid max pooling, but also propose the pyramid random pooling, which can pick the activation within each pooling region. First, the features obtained from the poolings are used to train weak single kernel SVM classifiers, which then are combined through MKB into a strong classifier. Numerous experiments on challenging datasets show that our tracking framework achieves promising.
A 70 GHz Cascaded Multi-Stage Distributed Amplifier in 90 nm CMOS Technology

A broadband cascaded multi-stage distributed amplifier (CMSDA) is proposed and implemented in a standard 90nm CMOS technology. The standard CMOS technology can offer gain, bandwidth, and power performances comparable to advanced compound semiconductor technologies [1]-[4]. The CMOS CMSDA can achieve better than 7dB gain with a bandwidth of 70GHz. The measured 1dB compression point (P1dB) is 10dBm at 30GHz, the input IP3 (IIP3) is 9.3dBm at 40GHz, and the average noise figure (NF) is 6.4dB from 1 to 25GHz.
Semi-supervised microblog sentiment analysis using social relation and text similarity

Microblog Sentiment Analysis (MSA) is a popular and important theme in social networks. Microblog platform such as Twitter, can collect rich microblogging messages everyday. However, for MSA tasks, it is still difficult and costly to collect sufficient manual sentiment labels for training. There are rich unlabeled microblogging messages, but only a few manual labeled messages. In this paper, we propose a novel semi-supervised learning approach for MSA. Specifically, we make use of microblog-microblog relations to build a graph-based semi-supervised classifier. We incorporate social relations and text similarities into building microblog-microblog relations. Our model connects labeled data and unlabeled data via microblog-microblog relations. Experiments on two real-world datasets show that our graph-based semi-supervised model outperforms the existing state-of-the-art models.
Person appearance modeling and orientation estimation using Spherical Harmonics

We present a novel approach for the joint estimation of a person's overall body orientation, 3D shape and texture, from overlapping cameras. Overall body orientation (i.e. rotation around torso major axis) is estimated by minimizing the difference between a learned texture model in a canonical orientation and a texture sampled using the current 3D shape estimate (i.e. torso and head). The estimated body orientation subsequently allows to update the 3D shape estimate, taking into account the new 3D shape measurement obtained by volume carving. Our main contribution is a method for estimating a person's relative body orientation while simultaneously generating a basic Spherical Harmonics based model of the person's shape and texture. Experiments show that the proposed method outperforms two state-of-the-art orientation estimation methods: one combining a fixed 3D shape model with a generate-and-test texture matching approach and one using a classifier based approach.
Meta-modèles et modèles pour l'intégration et l'interopérabilité des applications d'entreprises de production

L'integration des systemes consiste a assembler les differentes parties d'un systeme tout en assurant la compatibilite de l'assemblage ainsi que le bon fonctionnement du systeme complet. Depuis les annees quatre-vingt-dix, l'integration des systemes d'entreprise a fait l'objet d'une attention croissante ; elle est ainsi devenue un theme de recherche developpe dans plusieurs equipes universitaires et industrielles dans le monde autant que a suscite de nombreux travaux au sein des organisations scientifiques internationales, notamment IFAC et IFIP, et de normalisation, particulierement IEC, ISO et CEN. Dans ce cadre, l'interoperabilite des systemes est un moyen pour obtenir l'integration, fonde sur un couplage faible des parties du systeme, base sur la capacite des parties a communiquer entre elles pour acceder et faire appel a leurs fonctionnalites. Plus recemment, au cours de la derniere decennie, une nouvelle approche d'ingenierie logicielle a ete elaboree : l'ingenierie dirigee par les modeles. Dans cette nouvelle approche, les modeles occupent une place de premier plan parmi les artefacts d'ingenierie des systemes. En effet, ils doivent etre suffisamment precis afin de pouvoir etre interpretes ou transformes par des outils logiciels, tout en etant mis en correspondance avec les demarches d'ingenierie systeme. Le role central des modeles dans le developpement des capacites d'interoperabilite participe notablement a cette qualite, car les processus d'ingenierie de l'interoperabilite des applications sont bases sur des flux de modeles. Ce memoire d'Habilitation a Diriger des Recherches est centre sur l'etude des modeles en vue de l'interoperabilite des systemes, et plus particulierement des systemes d'entreprises, centree sur la representation des produits. Pour contribuer a la fiabilisation des modeles d'entreprise et de leur interrelations pour l'integration forte des applications, le projet de recherche propose dans ce memoire a pour objectif, dans un contexte d'ingenierie systeme applique aux systemes de systemes, de definir, d'etendre et de formaliser les processus de modelisation des systemes d'entreprise en tenant compte des connaissances, generalement non explicites, des acteurs de ces systemes. Cette preuve de concept relatif a la formalisation de la connaissance des modeles se base sur la definition d'ontologies, ainsi que la mise en correspondance, la transformation et l'echange de modeles, permettant l'integration des applications d'entreprise et assurant ainsi des flux d'informations coherents entre tous les acteurs. Ils necessitent ainsi de rendre explicite la connaissance tacite des modelisateurs (et operateurs) sur les processus (et donc les modeles) dont ils sont responsables ou auteurs.
PENGEMBANGAN BERTANYA KRITIS BERBASIS INKUIRI (BKBI) UNTUK PEMBELAJARAN KIMIA

Abstract: Curriculum 2013 recommended that the learning is done with a scientific approach. The key to the success of this learning approach is the student ability to ask critical questioning. Some studies of chemistry learning show students have difficulty to ask critical questions (Katchevich & Hofstein, 2013; Eshach et al., 2014; Santoso, 2014). These problem can certainly reduce the level of activity of students in constructing their own knowledge based on what is becoming a problem for him. To overcome these problems, it is necessary the development of inquiry learning that involves students asking question during the learning takes place. This article describes the development of learning “critical question - inquiry based for learning Chemistry", which is derived from theoretical studies that have been validated by several experts of learning science. Key words: ask question, inquiry Abstrak: Kurikulum 2013 merekomendasikan agar pembelajaran dilakukan dengan pendekatan ilmiah ( scientific approach ). Kunci keberhasilan pendekatan pembelajaran ini adalah kemampuan siswa mengajukan pertanyaan kritis. Beberapa hasil studi pembelajaran kimia terungkap bahwa pertanyaan siswa yang muncul sangat sederhana dengan frekuensi aktivitas mengajukan pertanyaan rendah (Katchevich & Hofstein,2013; Eshach et al ., 2014; Santoso, 2014). Keadaan seperti ini tentu dapat mengurangi tingkat aktivitas mahasiswa dalam membangun pengetahuan mereka sendiri berdasarkan apa yang menjadi masalah bagi dirinya. Untuk mengatasi permasalahan tersebut, perlu pengembangan pembelajaran inkuiri yang melibatkan siswa bertanya selama pembelajaran berlangsung. Artikel ini memaparkan pengembangan pembelajaran “bertanya kritis berbasis inkuiri (BKBI) untuk pembelajaran Kimia”, yang diperoleh dari hasil kajian teoritik yang telah divalidasi oleh beberapa ahli pembelajaran sains. Kata kunci : bertanya, inkuiri
Computer Aided Diagnostic Support System for Skin Cancer: A Review of Techniques and Algorithms

Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.
Quasi-Markets, Competition, and School Choice Lotteries

This article problematizes the lottery as a taken-for-granted concept, which is normatively understood as a neutral process rewarding its participant based on luck. The article adopts a policy problematization frame that interrogates the limits of normative concepts. To problematize the lottery system, this article engages with the two movies on school choice, The Lottery and Waiting for “Superman”, as “instances” through the conceptual lens of a quasi-market. The main argument is that the lottery is a particular discursive practice co-constituting the competitive frame of education quasi-markets. In identifying how the spirit of competitiveness underlies a competition, and by extension the lottery system, the article posits that in a competitive setting, competitors are primarily concerned with maximizing inequality among each other.
Explanation-mediated vision: making sense of the world through causal analysis

A long-standing and widely acknowledged problem in artificial intelligence is the dissociation of perception and cognition. This dissociation has led, on one hand, to cognitive models that bear uncertain relation to the problems of purposefully interacting with the world, and on the other hand to perceptual algorithms that produce data whose meaning and relevance is usually unknown, if considered at all. In this thesis I argue that the key to integrating perception and cognition is the development of good domain models of the perceptual world, describing the causality of the physical world, how that causality is manifest in the activity of the senses, and how special aspects of that causality are privileged as "functional," or goal-related. To support this argument I describe a number of artificial vision systems in which "perceptual" and "cognitive" computations interact and constrain each other via causal-perceptual models. These systems produce meaningful explanations of the internal dynamics of scenes. These explanations support a variety of high-level intelligent behaviors, including planning, robotic manipulation, and design evaluation. In the course of scene analysis, these systems use functional and causal anomalies in ongoing explanations to generate visual queries, thus providing control of focus of attention in low-level visual processing. The causal models employed by these systems are relatively small, but sufficiently powerful to generate explanations of highly complex structures. Much of these models can be recycled between visually disparate domains, suggesting wide generality. Given the success of these models, I consider the prospects for a cognitive psychology of vision, in which the knowledge that drives human visual understanding can be captured, formalized, and deployed in machines.
Prevention of Type 2 Diabetes (T2DM) in South Africa - a Focus on Facilitating Physical Activity Behaviour Change in Peri-Urban Youth

This paper focuses on type 2 diabetes mellitus (T2DM), and the significant health implications it has on individuals living in currently disadvantaged peri-urban areas in South Africa. Given the significant public health and socio-economic burden South Africa faces due to scarce resources and escalating rates of chronic diseases, prevention strategies which impact on modifiable risk factors for T2DM are vital. The population of interest was children and adolescents living in informal settlements on the outskirts of Cape Town. The suggested behaviour change was the increase and maintenance of a more physically active and healthy lifestyle, thereby facilitating weight loss and lowering the risk for developing T2DM. Brief motivational interviewing (BMI) based interventions, aimed at encouraging children and adolescents to modify their behaviour patterns are introduced. Transformative communication, self-efficacy and social support are also emphasised as crucial factors contributing to the promotion and maintenance of the desired health behaviour changes. Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. This article is available in Online Readings in Psychology and Culture: http://scholarworks.gvsu. edu/orpc/vol10/iss1/4
Identifying Reaction Functions in a Differential Oligopoly Game with Sticky Prices

We investigate the issue of strategic substitutability/complementarity in a Cournot differential game with sticky prices. We show that first order conditions do not produce instantaneous best reply functions. However, we identify negatively sloped reaction functions in steady state, with the open-loop best reply being flatter than its closed-loop counterpart.