Miracle-dz/UniFAR-FTUs huggingface dataset:
Conformational-Dependent and Independent RNA Binding to the Fragile X Mental Retardation Protein

The interaction between the fragile X mental retardation protein (FMRP) and BC1 RNA has been the subject of controversy. We probed the parameters of RNA binding to FMRP in several ways. Nondenaturing agarose gel analysis showed that BC1 RNA transcripts produced by in vitro transcription contain a population of conformers, which can be modulated by preannealing. Accordingly, FMRP differentially binds to the annealed and unannealed conformer populations. Using partial RNase digestion, we demonstrate that annealed BC1 RNA contains a unique conformer that FMRP likely binds. We further demonstrate that this interaction is 100-fold weaker than that the binding of eEF-1A mRNA and FMRP, and that preannealing is not a general requirement for FMRP's interaction with RNA. In addition, binding does not require the N-terminal 204 amino acids of FMRP, methylated arginine residues and can be recapitulated by both fragile X paralogs. Altogether, our data continue to support a model in which BC1 RNA functions independently of FMRP.
Roll up nanowire battery from silicon chips

Here we report an approach to roll out Li-ion battery components from silicon chips by a continuous and repeatable etch-infiltrate-peel cycle. Vertically aligned silicon nanowires etched from recycled silicon wafers are captured in a polymer matrix that operates as Li+ gel-electrolyte and electrode separator and peeled off to make multiple battery devices out of a single wafer. Porous, electrically interconnected copper nanoshells are conformally deposited around the silicon nanowires to stabilize the electrodes over extended cycles and provide efficient current collection. Using the above developed process we demonstrate an operational full cell 3.4 V lithium-polymer silicon nanowire (LIPOSIL) battery which is mechanically flexible and scalable to large dimensions.
Computerspiel- und Internetsucht: Diagnostik, Phänomenologie, Pathogenese und Therapie

Excessive computer gaming and internet use is becomming a growing matter of scientific und therapeutic interest. Results from epidemiologic research show that especially adolescents and young adults are in danger of excessive use patterns. Statistics from German addiction treatment centres reveal a growing number of patients experiencing addiction-like symptoms when using computer games or the internet. The similarity to substance-related addiction is emphasized by first neurobiological studies indicating typical cortical mechanisms underlying so called Computer Game and Internet Addiction. Despite a lack of consensus concerning classification and diagnostics Computer Game and Internet Addiction may will play a role in psychotherapeutic treatment in future. The paper offers a review of literature on Computergame and Internet Addiction in terms of scientific research and therapeutic intervention. This includes results from epidemiology, queries on diagnostics and etiopathological processes. Moreover aspects of prevention and intervention will be discussed.
Fast matrix multiplication techniques based on the Adleman-Lipton model

On distributed memory electronic computers, the implementation and association of fast parallel matrix multiplication algorithms has yielded astounding results and insights. In this discourse, we use the tools of molecular biology to demonstrate the theoretical encoding of Strassen’s fast matrix multiplication algorithm with DNA based on an n-moduli set in the residue number system, thereby demonstrating the viability of computational mathematics with DNA. As a result, a general scalable implementation of this model in the DNA computing paradigm is presented and can be generalized to the application of all fast matrix multiplication algorithms on a DNA computer. We also discuss the practical capabilities and issues of this scalable implementation. Fast methods of matrix computations with DNA are important because they also allow for the efficient implementation of other algorithms (that is inversion, computing determinants, and graph theory) with DNA. Key words: DNA computing, residue number system, logic and arithmetic operations, Strassen algorithm.
Coordinated Multiple Points Transmission for LTE-Advanced Systems

LTE-Advanced systems which based on orthogonal frequency division multiplexing (OFDM) can eliminate intra-cell interference but still can not mitigate inter-cell interference (ICI). Coordinated Multi-Point transmission/reception (CoMP) is one of the candidate techniques for LTE-Advanced systems to increase the average cell throughput and cell edge user throughput in the both uplink and downlink. Although CoMP naturally increases system complexity, it has potentially significant capacity and coverage benefits, making it worth a more detailed consideration. In this paper, we focus on the downlink CoMP-MU-MIMO transmission scheme and present some system level performance evaluation which shows that the CoMP-MU-MIMO transmission scheme can bring significant gains to both the average cell throughput and the cell edge user throughput.
Demo: a robust barcode system for data transmissions over screen-camera links

Visible light communication (VLC) over screen-camera links emerges as a novel form of near-field communication, and it offers a user-friendly, infrastructure-less and secure communication, which is highly competitive for one-time file transfer [1 - 4]. However, the limitations of smart devices and the uncertainty of user behaviors seriously impair the transmission reliability and hinder its applicability. Worse still, existing approaches [1, 2, 4]mostly focus on improving the transmission speed and ignore the transmission reliability. Hence, RDCode is proposed to boost the throughput over screen-camera links, by making use of a novel barcode design and several effective techniques to enhance the transmission reliability. In this demo, we show that our RDCode prototype system addresses many practical challenges. A short video on our prototype system is accessible from http://mashuai.buaa. edu.cn/demo/RDCode.mp4.
How to Read Your Own Mind : A Cognitive Theory of Self-Consciousness

The topic of self-awareness has an impressive philosophical pedigree, and sustained discussion of the topic goes back at least to Descartes. More recently, selfawareness has become a lively issue in the cognitive sciences, thanks largely to the emerging body of work on “mindreading”, the process of attributing mental states to people (and other organisms). During the last 15 years, the processes underlying mindreading have been a major focus of attention in cognitive and developmental psychology. Most of this work has been concerned with the processes underlying the attribution of mental states to other people. However, a number of psychologists and philosophers have also proposed accounts of the mechanisms underlying the attribution of mental states to oneself. This process of reading one’s own mind or becoming selfaware will be our primary concern in this paper.
The CSR green halo effect on the corporate–public communication: an experimental study

ABSTRACT Environmental corporate social responsibility (CSR) has been a popular practice among corporations. However, the mechanism and effectiveness of environmental CSR in affecting corporate–public communication are still unclear. Against the theoretical backdrop of the ‘halo effect’ and through a controlled experiment with 742 participants from Hong Kong and mainland China, we find that: if a company’s environmental CSR activity receives higher support from the consumers, it is less likely for consumers to avoid advertisements endorsed by the company. The CSR green halo effect therefore exists. Moreover, consumers’ nationality and their three preexisting attitudes (general environmental CSR support, environmental beliefs, and favorability of products’ country of origin) are important moderators of the green halo effect and need to be considered in practice.
Mediated intimacy in families: understanding the relation between children and parents

Mediating intimacy between children and their parents is still limited investigated and at the same time, we find that, emerging technologies are about to change and affect the way we interact with each other. In this paper, we report from an empirical study where we investigated the social interaction phenomena that unfold between children and their parents. We used cultural probes and contextual interviews to investigate the intimate acts between children and parents in three families. Our findings show that the intimate act between children and parents share a number of similarities with other types of intimate relations such as strong-tie intimacy (couples cohabiting). However, we also identified several issues of intimacy unique to the special relation between children and their parents. These unique acts of intimacy propose challenges when designing technologies for mediated intimacy in families.
Column-stored system join optimization on coupled CPU-GPU architecture

Heterogeneous architecture is the new trend of the development of Computer system central processor unit (CPU). Taking advantage of its powerful computer power has been a new research hotspot in database system field. First, in order to enhance the query performance of column-oriented database, we propose a data partition model which is environment sensitive. The data partition model provides optimal data division for every processing unit dynamically, by monitoring the CPU occupancy rate. Then, for GPU memory access optimization, we propose a DFAT estimate model for prefetching. At the same time, we optimize GPU memory access based on coalesced access; We implement a sort-merge join algorithm on a PC with an integrated CPU-GPU chip, which adopts our data partition model and our cost model in prefetching. Our strategy is able to distribute data to different processing units automatically, and can make sort-merge join achieve a performance improvement of 33% on coupled CPU-GPU architecture.
Navigating Imagined Audiences: Motivations for Participating in the Online Public Sphere

Little is known about why and how people use multiple social media platforms for political participation, or about the contexts through which social media is appropriated. This paper reports on a qualitative interview study of social media use by politically interested citizens. We interviewed 27 residents of the state of Hawaii who integrated one or more social media tools into their daily lives to participate in the online public sphere. Different social media environments offer both different affordances for action and different audiences, and we describe how media choice is driven by the match between motivations and affordances, and also by the imagined audience. We identified a number of motivations including understanding different viewpoints, formulating perspectives, engaging in positive discourse, repairing Hawaii's image, increasing political awareness and improving civic engagement. We discuss how these goals relate to both intrinsic and extrinsic motivations. Finally, we examine how social media choice and satisfaction were tied to the physical world context and people's sense of the audience within any particular medium.
Natural Language Processing 576 6 Comparison with Related Approaches 4 Grammatical Predicates for Textual Ellipsis Natural Language Processing 574 Natural Language Processing 573 a Conceptual Reasoning Approach to Textual Ellipsis

the centering model [6] to which we adhere is not considered a semantic theory but rather a discourse processing model which lends itself to an easy integration into a text understanding framework. Still, it does not provide for well-developed methods for textual ellipsis resolution. Grosz et al. rather sketchily point to the difference between the relations directly realizes and realizes whose precise definition they suggest depends on the semantic theory one adopts [6, p.209]. We have shown, however, that there are a lot of constraints at the conceptual level which cannot reasonably be accounted for by semantic theories. Only few NLP systems exist which deal with textual ellipsis in a dedicated way. For example, the PUNDIT system [17] provides a fairly restricted solution in that only direct conceptual links between the concept denoted by the antecedentand the elliptical expression are considered (" plausible " paths of length 1, in our terminology). The approach reported in this paper also extends our own previous work on textual ellipses [7] by the incorporation of an elaborated model of functional preferences on Cf elements which constrains the set of possible antecedents according to information structure criteria. 7 Conclusions In this paper, we have outlined a model of textual ellipsis resolution. It considers conceptual criteria to be of primary importance and provides conceptual well-formedness and strength criteria for role chains in a terminological knowledge base in order to assess the plausibil-ity of various possible antecedents as proper bridges [3] to elliptical expressions. Functional constraints based on the utterances' information structure contribute further restrictions on proper elliptical antecedents and require a basic revision of the centering model. The two principled difficulties inherent in every network-based symbolic knowledge representation approach are its dependency on hand-crafted and often domain-specific knowledge and the exorbitant costs for unconstrained search (often limiting the scalability of the approach). We cope with the first of these problems by postulating two formal criteria, viz. the non-cyclicity and the inclusion condition, which only depend on features present in almost any knowledge representation language, i.e., isa links, domains and ranges of relations and inverse relations. No reference to a specific network structure or a specific domain is made. The definition of patterns relies mainly on structural properties of semantic relations, which are entirely domain-independent. However, this heuristic criterion is only effective when the underlying knowledge base is built on top of a clear taxonomy of relations …
A proof of Hirschman Uncertainty invariance to the order of Rényi entropy for Picket Fence signals, and its relevance in a simplistic recognition experiment

In [1] we developed a new uncertainty measure which incorporates Rényi entropy instead of Shannon entropy. This new uncertainty measure was conjectured to be invariant to the Rényi order α > 0 for the case of the optimizer signals of Hirschman Uncertainty (Picket Fence functions whose lengths are a perfect square). In this paper, we prove this invariance, and test whether this invariance is predictive in the problem of a simple texture classification for digital images. In the preliminary results, we find that it certainly influences the recognizer performance. Specifically, we find that the recognition performance does not depend significantly on the Rényi parameter α. We hope that these results will be extended to other problems where Rényi entropy is used.
Transducer State Prediction System for Smart Environment Intelligent Control

Smart environments possess devices that collaborate to help the user non-intrusively. One possible aid smart environment offer is to anticipate user's tasks and perform them on his/her behalf or facilitate the action completion. In this paper, we propose a framework that predicts user's actions by learning his/her behavior when interacting with the smart environment. We prepare the datasets and train a predictor that is responsible to decide whether a target transducer value should be changed or not. Our solution achieves a significant improvement for all target transducers studied and most combinations of parameters yields better results than the base case.
A Taxonomy of Model Transformation and its Application to Graph Transformation

This article proposes a taxonomy of model transformation, based on the discussions of a working group on model transformation of the Dagstuhl seminar on Language Engineering for Model-Driven Software Development. This taxonomy can be used to help developers in deciding which model transformation approach is best suited to deal with a particular problem. We validate the taxonomy by applying it to graph transformation, a promising technology to deal with model transformation.
GPS-Based Vehicle Moving State Recognition Method and Its Applications on Dynamic In-Car Navigation Systems

In order to effectively determine whether a vehicle is turning or not, we proposed a method to map arbitrary consecutive GPS heading information to 2 dimensional feature space. Then we applied K-means clustering algorithm to divide the feature space into 2 classes: going straight and turning. After that, we used supervised learning algorithm to analyze these labeled data and build a model to recognize vehicle moving state. The experimental results showed that the model built in this way has good generalization. Based on the above research achievement, we designed and implemented a vehicle moving state recognition learning system for dynamic in-car navigation systems and applied this learning system to the map-matching field. The improved map-matching algorithm was tested on a complex urban road network and the result showed that the new algorithm can significantly improve the performance of the junction match.
The high velocity outflow in NGC 6334 I

Aims. We observed the high velocity outflow originating from NGC 6334 I in several CO transitions with the APEX telescope, with the goal of deriving the physical parameters of the gas. Methods. Using an LVG analysis, we studied line ratios between the CO(3–2), CO(4–3), and CO(7–6) data as a function of the density and of the kinetic temperature of the gas. An upper limit on the CO column density is derived by comparison with 13 CO data. Results. We constrained the temperature to be higher than 50 K and the H 2 density to values higher than $n\sim 10^4$ cm -3 towards the peak position in the red lobe, while $T>15$ K and $n>10^3$ cm -3 are derived towards the peak position in the blue lobe. The physical parameters of the outflow, its mass and its energetics, have been computed using the temperatures derived from this analysis. Conclusions. We conclude that high kinetic temperatures are present in the outflow and traced by high excitation CO lines. Observations of high- J CO lines are thus needed to infer reliable values of the kinetic temperatures and of the other physical parameters in outflows.
Trust and privacy correlations in social networks: A deep learning framework

Online Social Networks (OSNs) remain the focal point of Internet usage. Since the beginning, networking sites tried best to have right privacy mechanisms in place for users, enabling them to share the right content with the right audience. With all these efforts, privacy customizations remain hard for users across the sites. Existing research that address this problem mainly focus on semi-supervised strategies that introduce extra complexity by requiring the user to manually specify initial privacy preferences for their friends. In this work, we suggest an adaptive solution that can dynamically generate privacy labels for users in OSNs. To this end, we introduce a deep reinforcement learning framework that targets two key problems in OSNs like Facebook: the exposure of users' interactions through the network to less trusted direct friends, and the possibility of propagating user updates through direct friends' interactions to indirect friends. By implementing this framework, we aim at understanding how social trust and privacy could be correlated, specifically in a dynamic fashion. We report the ranked dependence between the generated privacy labels and the estimated user trust values, which indicate the ability of the framework to identify the highly trusted users and share with them higher percentages of data.
Targeted Mesoporous Iron Oxide Nanoparticles-Encapsulated Perfluorohexane and a Hydrophobic Drug for Deep Tumor Penetration and Therapy

A magneto-responsive energy/drug carrier that enhances deep tumor penetration with a porous nano-composite is constructed by using a tumor-targeted lactoferrin (Lf) bio-gate as a cap on mesoporous iron oxide nanoparticles (MIONs). With a large payload of a gas-generated molecule, perfluorohexane (PFH), and a hydrophobic anti-cancer drug, paclitaxel (PTX), Lf-MIONs can simultaneously perform bursting gas generation and on-demand drug release upon high-frequency magnetic field (MF) exposure. Biocompatible PFH was chosen and encapsulated in MIONs due to its favorable phase transition temperature (56 °C) and its hydrophobicity. After a short-duration MF treatment induces heat generation, the local pressure increase via the gasifying of the PFH embedded in MION can substantially rupture the three-dimensional tumor spheroids in vitro as well as enhance drug and carrier penetration. As the MF treatment duration increases, Lf-MIONs entering the tumor spheroids provide an intense heat and burst-like drug release, leading to superior drug delivery and deep tumor thermo-chemo-therapy. With their high efficiency for targeting tumors, Lf-MIONs/PTX-PFH suppressed subcutaneous tumors in 16 days after a single MF exposure. This work presents the first study of using MF-induced PFH gasification as a deep tumor-penetrating agent for drug delivery.
MLPA screening in the BRCA1 gene from 1,506 German hereditary breast cancer cases: novel deletions, frequent involvement of exon 17, and occurrence in single early‐onset cases

We present a comprehensive analysis of 1,506 German families for large genomic rearrangements (LGRs) in the BRCA1 gene and of 450 families in the BRCA2 gene by the multiplex ligation‐dependent probe amplification (MLPA) technique. A total of 32 pathogenic rearrangements in the BRCA1 gene were found, accounting for 1.6% of all mutations, but for 9.6% of all BRCA1 mutations identified in a total of 1,996 families, including 490 with small pathogenic BRCA1/2 mutations. Considering only high risk groups for hereditary breast/ovarian cancer, the prevalence of rearrangements is 2.1%. Interestingly, deletions involving exon 17 of the BRCA1 gene seem to be most frequent in Germany. Apart from recurrent aberrations like del ex17, dupl ex13, and del ex22, accounting for more than 50% of all BRCA1 LGRs, we could fully characterize 11 novel deletions. Moreover, one novel deletion involving exons 1–7 and one deletion affecting the entire BRCA1 gene were identified. All rearrangements were detected in families with: 1) at least two breast cancer cases prior to the age of 51 years; 2) breast and ovarian cancer cases; 3) ovarian cancer only families with at least two ovarian cancer cases; or 4) a single breast cancer case prior to the age of 36 years, while no mutations were detected in breast cancer only families with no or only one breast cancer case prior to the age of 51 years. Analysis for gross rearrangements in 412 high‐risk individuals, revealed no event in the BRCA2 gene and only two known CHEK2 mutations. However, in an additional 38 high‐risk families with cooccurrence of female breast/ovarian and male breast cancer, one rearrangement in the BRCA2 gene was found. In summary, we advise restricting BRCA1 MLPA screening to those subgroups that revealed LGRs and recommend BRCA2 MLPA screening only for families presenting with cooccurrence of female and male breast cancer. Hum Mutat 29(7), 948–958, 2008. © 2008 Wiley‐Liss, Inc.