Tailoring Plasmonic Metamaterials for Ultrasenstive Detection of Mercury Trace Contaminants via Molecular Logic Gates

Structural and functional information encoded in DNA combined with unique properties of nanomaterials could be of use for the construction of novel biocomputational circuits and intelligent biomedical nanodevices. However, at present their practical applications are still limited by either low reproducibility of fabrication, modest sensitivity, or complicated handling procedures. Here, we demonstrate the construction of label-free and switchable molecular logic gates (AND, INHIBIT, and OR) that use specific conformation modulation of a guanine- and thymine-rich DNA, while the optical readout is enabled by the tunable metamaterials which serve as a substrate for surface enhanced Raman spectroscopy (MetaSERS). Our MetaSERS-based DNA logic is simple to operate, highly reproducible, and can be stimulated by ultra-low concentration of the external inputs, enabling an extremely sensitive detection of mercury ions down to 2×10-4 ppb, which is four orders of magnitude lower than the exposure limit allowed by United States Environmental Protection Agency

Spatial and temporal influences of in-stream factors on the chemistry and epilithic biomasses of upland stream metal deposits

The density and composition of stream bed metal deposits are affected by physical, chemical and biological processes. In this paper we investigate the importance of these processes and their relation to algal and non-photosynthetic detrital (NPD) biomass in a set of upland streams in Northern Ireland. Deposit density and Fe, Mn, Al and P concentrations varied with stream pH across sites but not seasonally. No effects of stream bed erosion or photoreduction were detected on deposit densities. Seasonal variation in stream water metal concentrations was correlated with rainfall. NPD biomass was a significant predictor of both spatial and seasonal variation in deposit concentrations. There were strong, non-linear, relations between NPD biomass and deposit metal concentrations, with Fe and Mn becoming relatively more important and algal biomass declining above threshold deposit/NPD densities. The results suggest that NPD biomass influences deposit density and reduces the biomass of photosynthetic autotrophs above a threshold deposit density.

Energy versus data integrity trade-offs in embedded high-density logic compatible dynamic memories

Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

A Steganalysis System Utilizing Temporal Pixel Correlation Of HEVC Video

High Efficiency Video Coding (HEVC) is the most recent video codec coming after currently most popular H.264/MPEG4 codecs and has promising compression capabilities. It is conjectured that it will be a substitute for current video compression standards. However, to the best knowledge of the authors, none of the current video steganalysis methods designed or tested with HEVC video. In this paper, pixel domain steganography applied on HEVC video is targeted for the first time. Also, its the first paper that employs accordion unfolding transformation, which merges temporal and spatial correlation, in pixel domain video steganalysis. With help of the transformation, temporal correlation is incorporated into the system. Its demonstrated for three different feature sets that integrating temporal dependency substantially increased the detection accuracy.

Spatio-Temporal Rich Model For Motion Vector Steganalysis

We propose a spatio-temporal rich model of motion vector planes as a part of a full steganalytic system against motion vector based steganography. Superior detection accuracy of the rich model over the previous methods has been lately demonstrated for digital images in both spatial and DCT domain. It has not been heretofore used for detection of motion vector steganography. We also introduced a transformation so as to extend the feature set with temporal residuals. We carried out the tests along with most recent motion vector steganalysis and steganography methods. Test results show that the proposed model delivers an outstanding performance compared to the previous methods.

Detecting localized homogeneous anomalies over spatio-temporal data

The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as – weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases – i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.

Composition and temporal variation of the algal assemblage associated with the haplosclerid sponge Haliclona indistincta (Bowerbank)

Although interactions between seaweeds and sponges have been studied in detail, general information concerning the whole epibiontic algal assemblage associated with a sponge species is virtually non-existent. We present here the first study in which the macroalgal community associated with a sponge, Haliclona indistincta (Bowerbank), was examined in detail. In the period October 2009-September 2010, the seaweed assemblage epibiontic on H. indistincta at a site of the Irish West coast was composed of 66 algal taxa (48 red algae, 7 green algae, 11 brown algae). The red algae Gelidium spinosum and Rhodothamniella floridula were the only epibionts associated with H. indistincta for the whole annual cycle. Most of the algal epibionts were filamentous species, which colonized the surface of the sponge and did not penetrate deeply into it. The algal assemblage was most abundant and species-diverse in the period late winter-spring; multivariate analyses revealed a significant variation of the community on the temporal scale of season and sampling date (weeks to months). The results indicate that the algal communities associated with sponges may be very diverse, showing that this type of assemblage deserves further detailed studies. © 2012 Elsevier B.V.

Optical measurement of the temporal delay between two ultra-short and focussed laser pluses

Temporal overlapping of ultra-short and focussed laser pulses is a particularly challenging task, as this timescale lies orders of magnitude below the typical range of fast electronic devices. Here we present an optical technique that allows for the measurement of the temporal delay between two focussed and ultra-short laser pulses. This method is virtually applicable to any focussing geometry and relative intensity of the two lasers. Experimental implementation of this technique provides excellent quantitative agreement with theoretical expectations. The proposed technique will prove highly beneficial for high-power multiple-beam laser experiments.

Temporal structure of attosecond pulses from laser-driven coherent synchrotron emission

The microscopic dynamics of laser-driven coherent synchrotron emission transmitted through thin foils are investigated using particle-in-cell simulations. For normal incidence interactions, we identify the formation of two distinct electron nanobunches from which emission takes place each half-cycle of the driving laser pulse. These emissions are separated temporally by 130 attoseconds and are dominant in different frequency ranges, which is a direct consequence of the distinct characteristics of each electron nanobunch. This may be exploited through spectral filtering to isolate these emissions, generating electromagnetic pulses of duration ~70 as.

Logic Brightens My Day: Evidence for Implicit Sensitivity to Logical Validity.

A key assumption of dual process theory is that reasoning is an explicit, effortful, deliberative process. The present study offers evidence for an implicit, possibly intuitive component of reasoning. Participants were shown sentences embedded in logically valid or invalid arguments. Participants were not asked to reason but instead rated the sentences for liking (Experiment 1) and physical brightness (Experiments 2-3). Sentences that followed logically from preceding sentences were judged to be more likable and brighter. Two other factors thought to be linked to implicit processing-sentence believability and facial expression-had similar effects on liking and brightness ratings. The authors conclude that sensitivity to logical structure was implicit, occurring potentially automatically and outside of awareness. They discuss the results within a fluency misattribution framework and make reference to the literature on discourse comprehension. 

Climate drives temporal replacement and nested‐resultant richness patterns of Scottish coastal vegetation

Beta diversity quantifies spatial and/or temporal variation in species composition. It is comprised of two distinct components, species replacement and nestedness, which derive from opposing ecological processes. Using Scotland as a case study and a β-diversity partitioning framework, we investigate temporal replacement and nestedness patterns of coastal grassland species over a 34-yr time period. We aim to 1) understand the influence of two potentially pivotal processes (climate and land-use changes) on landscape-scale (5 × 5 km) temporal replacement and nestedness patterns, and 2) investigate whether patterns from one β-diversity component can mask observable patterns in the other.

We summarised key aspects of climate driven macro-ecological variation as measures of variance, long-term trends, between-year similarity and extremes, for three important climatic predictors (minimum temperature, water-balance and growing degree-days). Shifts in landscape-scale heterogeneity, a proxy of land-use change, was summarised as a spatial multiple-site dissimilarity measure. Together, these climatic and spatial predictors were used in a multi-model inference framework to gauge the relative contribution of each on temporal replacement and nestedness patterns.

Temporal β-diversity patterns were reasonably well explained by climate change but weakly explained by changes in landscape-scale heterogeneity. Climate was shown to have a greater influence on temporal nestedness than replacement patterns over our study period, linking nestedness patterns, as a result of imbalanced gains and losses, to climatic warming and extremes respectively. Important climatic predictors (i.e. growing degree-days) of temporal β-diversity were also identified, and contrasting patterns between the two β-diversity components revealed.

Results suggest climate influences plant species recruitment and establishment processes of Scotland's coastal grasslands, and while species extinctions take time, they are likely to be facilitated by climatic perturbations. Our findings also highlight the importance of distinguishing between different components of β-diversity, disentangling contrasting patterns than can mask one another.