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In this paper two groups supporting different views on the mechanism of light induced polymer deformation argue about the respective underlying theoretical conceptions, in order to bring this interesting debate to the attention of the scientific community. The group of Prof. Nicolae Hurduc supports the model claiming that the cyclic isomerization of azobenzenes may cause an athermal transition of the glassy azobenzene containing polymer into a fluid state, the so-called photo-fluidization concept. This concept is quite convenient for an intuitive understanding of the deformation process as an anisotropic flow of the polymer material. The group of Prof. Svetlana Santer supports the re-orientational model where the mass-transport of the polymer material accomplished during polymer deformation is stated to be generated by the light-induced re-orientation of the azobenzene side chains and as a consequence of the polymer backbone that in turn results in local mechanical stress, which is enough to irreversibly deform an azobenzene containing material even in the glassy state. For the debate we chose three polymers differing in the glass transition temperature, 32 degrees C, 87 degrees C and 95 degrees C, representing extreme cases of flexible and rigid materials. Polymer film deformation occurring during irradiation with different interference patterns is recorded using a homemade set-up combining an optical part for the generation of interference patterns and an atomic force microscope for acquiring the kinetics of film deformation. We also demonstrated the unique behaviour of azobenzene containing polymeric films to switch the topography in situ and reversibly by changing the irradiation conditions. We discuss the results of reversible deformation of three polymers induced by irradiation with intensity (IIP) and polarization (PIP) interference patterns, and the light of homogeneous intensity in terms of two approaches: the re-orientational and the photo-fluidization concepts. Both agree in that the formation of opto-mechanically induced stresses is a necessary prerequisite for the process of deformation. Using this argument, the deformation process can be characterized either as a flow or mass transport.
Individuals with agrammatic Broca's aphasia experience difficulty when processing reversible non-canonical sentences. Different accounts have been proposed to explain this phenomenon. The Trace Deletion account (Grodzinsky, 1995, 2000, 2006) attributes this deficit to an impairment in syntactic representations, whereas others (e.g., Caplan, Waters, Dede, Michaud, & Reddy, 2007; Haarmann, Just, & Carpenter, 1997) propose that the underlying structural representations are unimpaired, but sentence comprehension is affected by processing deficits, such as slow lexical activation, reduction in memory resources, slowed processing and/or intermittent deficiency, among others. We test the claims of two processing accounts, slowed processing and intermittent deficiency, and two versions of the Trace Deletion Hypothesis (TDH), in a computational framework for sentence processing (Lewis & Vasishth, 2005) implemented in ACT-R (Anderson, Byrne, Douglass, Lebiere, & Qin, 2004). The assumption of slowed processing is operationalized as slow procedural memory, so that each processing action is performed slower than normal, and intermittent deficiency as extra noise in the procedural memory, so that the parsing steps are more noisy than normal. We operationalize the TDH as an absence of trace information in the parse tree. To test the predictions of the models implementing these theories, we use the data from a German sentence—picture matching study reported in Hanne, Sekerina, Vasishth, Burchert, and De Bleser (2011). The data consist of offline (sentence-picture matching accuracies and response times) and online (eye fixation proportions) measures. From among the models considered, the model assuming that both slowed processing and intermittent deficiency are present emerges as the best model of sentence processing difficulty in aphasia. The modeling of individual differences suggests that, if we assume that patients have both slowed processing and intermittent deficiency, they have them in differing degrees.
A Conjunction of Mysteries
(2016)
Multimodal representation learning has gained increasing importance in various real-world multimedia applications. Most previous approaches focused on exploring inter-modal correlation by learning a common or intermediate space in a conventional way, e.g. Canonical Correlation Analysis (CCA). These works neglected the exploration of fusing multiple modalities at higher semantic level. In this paper, inspired by the success of deep networks in multimedia computing, we propose a novel unified deep neural framework for multimodal representation learning. To capture the high-level semantic correlations across modalities, we adopted deep learning feature as image representation and topic feature as text representation respectively. In joint model learning, a 5-layer neural network is designed and enforced with a supervised pre-training in the first 3 layers for intra-modal regularization. The extensive experiments on benchmark Wikipedia and MIR Flickr 25K datasets show that our approach achieves state-of-the-art results compare to both shallow and deep models in multimodal and cross-modal retrieval.
The molecular biomarker composition of two sediment cores from Sanabria Lake (NW Iberian Peninsula) and a survey of modern plants in the watershed provide a reconstruction of past vegetation and landscape dynamics since deglaciation. During a proglacial stage in Lake Sanabria (prior to 14.7 cal ka BP), very low biomarker concentration and carbon preference index (CPI) values similar to 1 suggest that the n-alkanes could have derived from eroded ancient sediment sources or older organic matter with high degree of maturity. During the Late glacial (14.7-11.7 cal ka BP) and the Holocene (last 11.7 cal ka BP) intervals with higher biomarker and triterpenoid concentrations (high %nC(29) , nC(31) alkanes), higher CPI and average carbon length (ACL), and lower P-aq (proportion of aquatic plants) are indicative of major contribution of vascular land plants from a more forested watershed (e.g. Mid Holocene period 7.0-4.0 cal ka BP). Lower biomarker concentrations (high %nC(27) alkanes), CPI and ACL values responded to short phases with decreased allochthonous contribution into the lake that correspond to centennial-scale periods of regional forest decline (e.g. 4-3 ka BP, Roman deforestation after 2.0 ka, and some phases of the LIA, seventeenth-nineteenth centuries). Human activities in the watershed were significant during early medieval times (1.3-1.0 cal ka BP) and since 1960 CE, in both cases associated with relatively higher productivity stages in the lake (lower biomarker and triterpenoid concentrations, high %nC(23) and %nC(31) respectively, lower ACL and CPI values and higher P-aq). The lipid composition of Sanabria Lake sediments indicates a major allochthonous (watershed-derived) contribution to the organic matter budget since deglaciation, and a dominant oligotrophic status during the lake history. The study constrains the climate and anthropogenic forcings and watershed versus lake sources in organic matter accumulation processes and helps to design conservation and management policies in mountain, oligotrophic lakes.
In Near Edge X-Ray Absorption Fine Structure (NEXAFS) spectroscopy X-Ray photons are used to excite tightly bound core electrons to low-lying unoccupied orbitals of the system. This technique offers insight into the electronic structure of the system as well as useful structural information. In this work, we apply NEXAFS to two kinds of imidazolium based ionic liquids ([C(n)C(1)im](+)[NTf2](-) and [C(4)C(1)im](+)[I](-)). A combination of measurements and quantum chemical calculations of C K and N K NEXAFS resonances is presented. The simulations, based on the transition potential density functional theory method (TP-DFT), reproduce all characteristic features observed by the experiment. Furthermore, a detailed assignment of resonance features to excitation centers (carbon or nitrogen atoms) leads to a consistent interpretation of the spectra.
In Near Edge X-Ray Absorption Fine Structure (NEXAFS) spectroscopy X-Ray photons are used to excite tightly bound core electrons to low-lying unoccupied orbitals of the system. This technique offers insight into the electronic structure of the system as well as useful structural information. In this work, we apply NEXAFS to two kinds of imidazolium based ionic liquids ([CnC1im]+[NTf2]- and [C4C1im]+[I]-). A combination of measurements and quantum chemical calculations of C K and N K NEXAFS resonances is presented. The simulations, based on the transition potential density functional theory method (TP-DFT), reproduce all characteristic features observed by the experiment. Furthermore, a detailed assignment of resonance features to excitation centers (carbon or nitrogen atoms) leads to a consistent interpretation of the spectra.
When sampling animal movement paths, the frequency at which location measurements are attempted is a critical feature for data analysis. Important quantities derived from raw data, e.g. travel distance or sinuosity, can differ largely based on the temporal resolution of the data. Likewise, when movement models are fitted to data, parameter estimates have been demonstrated to vary with sampling rate. Thus, biological statements derived from such analyses can only be made with respect to the resolution of the underlying data, limiting extrapolation of results and comparison between studies. To address this problem, we investigate whether there are models that are robust against changes in temporal resolution. First, we propose a mathematically rigorous framework, in which we formally define robustness as a model property. We then use the framework for a thorough assessment of a range of basic random walk models, in which we also show how robustness relates to other probabilistic concepts. While we found robustness to be a strong condition met by few models only, we suggest a new method to extend models so as to make them robust. Our framework provides a new systematic, mathematically founded approach to the question if, and how, sampling rate of movement paths affects statistical inference.
The outermost cell layer of plants, the epidermis, and its outer (lateral) membrane domain facing the environment are continuously challenged by biotic and abiotic stresses. Therefore, the epidermis and the outer membrane domain provide important selective and protective barriers. However, only a small number of specifically outer membrane-localized proteins are known. Similarly, molecular mechanisms underlying the trafficking and the polar placement of outer membrane domain proteins require further exploration. Here, we demonstrate that ACTIN7 (ACT7) mediates trafficking of the PENETRATION3 (PEN3) outer membrane protein from the trans-Golgi network (TGN) to the plasma membrane in the root epidermis of Arabidopsis (Arabidopsis thaliana) and that actin function contributes to PEN3 endocytic recycling. In contrast to such generic ACT7-dependent trafficking from the TGN, the EXOCYST84b (EXO84b) tethering factor mediates PEN3 outer-membrane polarity. Moreover, precise EXO84b placement at the outer membrane domain itself requires ACT7 function. Hence, our results uncover spatially and mechanistically distinct requirements for ACT7 function during outer lateral membrane cargo trafficking and polarity establishment. They further identify an exocyst tethering complex mediator of outer lateral membrane cargo polarity.