Spatio-temporal Reconstruction Research Articles

Axon hillock currents enable single-neuron-resolved 3D reconstruction using diamond nitrogen-vacancy magnetometry

Sensing neuronal action potential associated magnetic fields (APMFs) is an emerging viable alternative of functional brain mapping. Measurement of APMFs of large axons of worms have been possible due to their size. In the mammalian brain, axon sizes, their numbers and routes, restricts using such functional imaging methods. With a segmented model of mammalian pyramidal neurons, we show that the APMF of intra-axonal currents in the axon hillock are two orders of magnitude larger than other neuronal locations. Expected 2D magnetic field maps of naturalistic spiking activity of a volume of neurons via widefield diamond-nitrogen-vacancy-center-magnetometry were simulated. A dictionary-based matching pursuit type algorithm applied to the data using the axon-hillock’s APMF signature allowed spatiotemporal reconstruction of action potentials in the volume of brain tissue at single cell resolution. Enhancement of APMF signals coupled with magnetometry advances thus can potentially replace current functional brain mapping techniques.

Quantifying the effects of remnant seed sources on post-volcanic-eruption forest recovery through historic landscape reconstruction from 1710 to 2010

The rate and trajectory of forest landscape recovery after a volcanic eruption rely largely on available seed sources and patterns of seed dispersal. However, quantifying the importance of various seed sources has not been attempted. We demonstrate a forest landscape modeling framework for spatiotemporal reconstruction of post-volcanic-eruption forest landscape. We quantify the effects of remnant seed sources on post-eruption forest landscape recovery at tree species level in Changbai Mountain, China. We used a factorial experiment of modeled scenarios with/without remnant seed sources and/or matrix seed sources. We applied the modeling framework to reconstruct the post-eruption forest landscape from 1710 to 2010. Remnant seed sources’ contribution to basal area and density was minimum before year 1810 and 1770, and increased to maximum at 1940 (51%) and 1840 (79%), respectively. Remnant seed sources contributed > 40% to stand age from 1740 to 1870. Remnant seed sources’ contribution to species area was minimum at 1760 for all species, while it increased to > 40% at 2010 for some late-successional species. Remnant seed sources have relatively small effects in the early stage of post-volcanic-eruption forest landscape recovery. This is different from what has been reported of other disturbances such as wind and fire. Remnant seed sources facilitate late-successional species recovery, advance forest succession, and increase stand age. These findings coincide with reports of other types of disturbances. Spatiotemporal historic landscape reconstruction provides a platform to simulate seed dispersal and quantify the roles of remnant seed sources on post-disturbance landscape recovery.

Arctic Sea Ice in the First Half of the 20th Century: Temperature-Based Spatiotemporal Reconstruction

Arctic Sea Ice in the First Half of the 20th Century: Temperature-Based Spatiotemporal Reconstruction

Spatio-Temporal Reconstruction for 3D Motion Recovery

This paper addresses the challenge of 3D motion recovery by exploiting the spatio-temporal correlations of corrupted 3D skeleton sequences. We propose a new 3D motion recovery method using spatio-temporal reconstruction, which uses joint low-rank and sparse priors to exploit temporal correlation and an isometric constraint for spatial correlation. The proposed model is formulated as a constrained optimization problem, which is efficiently solved by the augmented Lagrangian method with a Gauss–Newton solver for the subproblem of isometric optimization. The experimental results on the CMU motion capture dataset, Edinburgh dataset, and two Kinect datasets demonstrate that the proposed approach achieves better motion recovery than the state-of-the-art methods. The proposed method is applicable to Kinect-like skeleton tracking devices and pose estimation methods that cannot provide accurate estimation of complex motions, especially in the presence of occlusion.

Three- and bi-dimensional analyses of the shoaling behavior in zebrafish: Influence of modulators of anxiety-like responses

Social behaviors are key components that play adaptive roles in various species, including humans. The zebrafish (Danio rerio) is a social species and the shoaling behavior can be pharmacologically manipulated either by anxiogenic or anxiolytic substances, providing translatable data in neuropsychiatric research. Here, we aimed to characterize the shoaling behavior in zebrafish under different pharmacological manipulations in a three-dimensional (3D) perspective using the spatial coordinates of the fish positions. Temporal and spatial reconstructions of shoal occupancy were performed after exposure to conspecific alarm substance (CAS) and caffeine (CAF) (anxiogenic substances) or diazepam (DZP) (a classical anxiolytic drug). Behavioral 3D analyses and spatiotemporal reconstructions of the shoaling behavior revealed that both CAS and CAF decreased the shoal volume, the average fish distance to the centoid point, and increased shoal geotaxis, but only CAS reduced the inter-fish distance when compared to control (CTRL). Conversely, DZP group showed increased shoal volume and inter-fish distance. Because substantial differences were verified when the shoaling response was analyzed in 3D and 2D perspectives, we reinforce the use of 3D reconstructions of fish positions to assess how different manipulations affect the social behavior of zebrafish. The novel procedure described here represents an easy-to-use, inexpensive, and alternative tool to perform a spatiotemporal reconstruction of the shoal occupancy under different pharmacological manipulations, complementing the existing quantification of locomotion activity of multiple fish.

Stable mechanical environments created by a low-tension traction device is beneficial for the regeneration and repair of degenerated intervertebral discs

BACKGROUNDBy blocking the cascade of reactions leading to intervertebral disc degeneration through immobilization-traction, a delay in intervertebral disc degeneration and its regeneration, to some extent, has been observed. However, the precise balance of regulation of the microenvironment of intervertebral disc biomechanics and coordination of the complex spatiotemporal reconstruction of the extracellular matrix have not yet been solved, and clinical results are far from successful. PURPOSEIn the present study, a mechanical degeneration model was constructed to evaluate the possibility and effectiveness of disc regeneration or repair through low-tension traction of degenerated discs so as to provide basic biomechanical information for clinical optimization of the traction device and to establish traction parameters for prevention and treatment of disc degeneration. STUDY DESIGNA macro-, micro-, and nano-level structural analysis of degenerative discs of rat tail before and after controlled traction. METHODSSix-month-old male Sprague-Dawley rats were randomly divided into seven groups: Group A: control group (instrumented with Kirschner [K]-wires only); Group B: Model group (caudal vertebrae immobilized using a custom-made external device to fix four caudal vertebrae [Co7−Co10], while Co8−Co9 vertebrae underwent 4 weeks of compression to induce disc degeneration); Group C: experimental control group (devices removed after the 4 week compression described in Group B, and recovered by themselves for 4 weeks). The remaining four groups represented intervention groups (Groups D and F: Co8−Co9 vertebrae compressed for 4 weeks followed by 2 or 4 weeks of in situ traction, respectively; Groups E and G: vertebrae compressed for 4 weeks followed by 2 or 4 weeks of excessive traction, respectively). X-ray and magnetic resonance imaging were performed at each time point to measure disc height and T2 signal intensity. At the end of the experiment, the animals were euthanized and tail vertebrae harvested for analysis of intervertebral disc histopathology, proteoglycan content, elastic modulus of fibers of the annulus fibrosus (AF) and nucleus pulposus (NP), and microstructure of the bony end plate. RESULTSAfter 2 to 4 weeks of continuous traction (in situ and excessive traction), the Co8–Co9 intervertebral disc space of rats in Groups D to G increased significantly compared with Groups B and C (p < .05). In addition, signs of tissue regeneration were apparent in all four intervention groups (D–G). In addition, histologic scores of the intervention groups (D–G) were significantly lower than those in the model and experimental control groups (Groups B and C, respectively), although no significant difference was found between those four groups. Compared with the model group (Group B), total proteoglycan content of the NP in the intervention groups (D–G) increased significantly (p < .05). After 2 to 4 weeks of intervention (in situ and excessive traction), the morphology of pores in the bony end plate, their number, and the diameter had recovered significantly compared with those in Group B. The in situ traction group was superior to the excessive traction group, and 4 weeks in situ group significantly superior to the 2 weeks group. In all intervention groups, in both the inner and outer AF, mean fibril diameter decreased significantly (p < .05), although they remained larger in the excessive traction group than that in the in situ traction group. Consistent with trend in collagen fiber diameter, the outer AF was stiffer than the inner, and the modulus of the AF in each intervention group not significantly different from that of the control group (Group A) except Group C. However, within the NP, the variation in trend in diameter and modulus of collagen fibers was essentially inconsistent with that of the AF. CONCLUSIONSDegenerated discs exhibit greater reconstruction after low tension traction. It is clear that the intervertebral disc mechanical microenvironment depends to a greater extent on low-tension traction than high-tension traction.

Spatiotemporal reconstruction of MODIS land surface temperature with the help of GLDAS product using kernel-based nonparametric data assimilation

Spatiotemporal inconsistency in MODIS land surface temperature (LST), one of the most widely used geospatial data parameters, is a concern for its application in various studies. Moreover, there are limited methods that can address spatiotemporal reconstruction of LST in diverse physiography. The use of kernel-based spatiotemporal assimilation in a multitemporal approach to reconstruct LST in a complex physiographic region, northeast India, is addressed. Global land skin temperature (Ts) from Global Land Data Assimilation System (GLDAS) is chosen as a temporal covariate for MODIS LST due to its consistent temporal resolution. Considering the high temporal correlation between GLDAS Ts and MODIS LST, temporal assimilation is done in the first stage followed by spatial assimilation in the second stage. Due to data gaps, a kernel-based nonparametric estimator is adopted to map the spatiotemporal distribution and reconstruct LST with spatiotemporal consistency. This approach shows satisfactory performance in restoration of spatial variation in the study area with a coefficient of determination (R2 = 0.98), root mean square error (RMSE = 0.61 K), and absolute value of bias (B = 0.22 K). Also, the credibility of reconstructed LST from this method is found to be as good as the baseline data (MODIS LST) given that there is no severe data deficiency with uneven spatial availability in the baseline data itself. Comparison of gap-filled LST showed positive correlation with ground-based measurements (average R = 0.71), reflecting decent agreement with seasonality. Hence, the kernel-based nonparametric assimilation could be used to reconstruct LST using a multitemporal approach in complex physiographic regions, which could be used to fill the spatiotemporal data gaps and increase data consistency in MODIS LST.

P203 Unsupervised one-class classification and anomaly detection of stress echocardiograms with deep denoising spatio-temporal autoencoders

Abstract Introduction The combination of medical knowledge, experience and AI algorithms have supported the advancement of patient care and the lowering of healthcare costs. Machine and deep learning methods enable the extraction of meaningful patterns that remain beyond human perception. Numerous computer-aided diagnosis and detection systems have been developed to assist in the assessment of stress echocardiograms. However, issues are encountered when facing imbalanced, limited, and unannotated datasets. Learning from imbalanced medical datasets impairs diagnostic accuracy due to classifier bias and overfitting. Furthermore, datasets comprising of all existing abnormal classes are impossible to obtain, hence supervised algorithms would fail to generate predictions for classes devoid of training samples. Moreover, reliance on prior knowledge in the form of expert annotation and anatomical region extraction impairs scalability, as these procedures are time-consuming, computationally expensive, and limited to specific tasks. Purpose We aimed to perform one-class classification and anomaly detection of stress echocardiograms using unsupervised deep learning techniques to discriminate between normal and abnormal videos as well as to localise wall motion abnormalities within individual frames. Methods Deep denoising spatio-temporal autoencoder networks were employed to learn visual and motion representations from multiple echocardiographic cross-sections and stress stages. Extracted middle layer features were modelled by one-class support vector machines to discriminate between regular and irregular echocardiograms despite the absence of abnormal training samples. Reconstruction errors allowed for direct visualisation and localisation of anomalous cardiac regions, without the need for annotated training data or segmentation of structures. Results 2D B-mode stress echocardiograms acquired from 36 patients were classified as normal or abnormal based on patient reports and served as the ground truth. Results revealed that learnt features extracted from spatio-temporal autoencoders trained solely on normal data can be utilised to classify abnormal echocardiograms with a high level of accuracy, sensitivity and specificity. In addition to that, as validated by an expert reader, spatio-temporal autoencoder reconstruction errors were capable of detecting and localising wall motion abnormalities in specific cardiac regions without prior knowledge of abnormal segments. Conclusions The trained model enables the classification and detection of spatio-temporal abnormalities in stress echocardiograms. Therefore, the proposed networks have the potential of assisting in the global and regional assessment of stress echocardiograms.

A statistical and numerical modeling approach for spatiotemporal reconstruction of glaciations in the Central Asian mountains

Reconstructing Quaternary regional glaciations throughout the Himalaya, Tibet, and the adjoining mountains in Central Asia is challenging due to geological biases towards limited preservation of glacial deposits and chronological uncertainties. Here, we offer several statistical and mathematical model codes in R, in excel, and in MATLAB useful to develop regional glacial chronostratigraphies, especially in areas with distinct orographically-modulated climate. A complete R code is provided to generate a regional climate map using Cluster Analysis (CA) and Principal Component Analysis (PCA). Additional R codes include reduced chi-squared, Chauvenet's criterion, radial plotter/abanico plot, finite mixture model, and Student's t-test. These methods are useful in reconstructing the timing of local and regional glacial chronologies. An excel code to calculate equilibrium-line altitudes (ELAs) and steps to reconstruct glacier hypsometry are also made available to further aid to our understanding of the extent of paleoglaciations. A MATLAB code of the linear glacier flow model is included to reconstruct paleotemperatures using the length and slope of a glacier during past advances.•R statistical codes can be used/modified without restrictions for other researchers.•Easy steps to calculate ELAs and glacier hypsometry from the same data.•Paleo-temperature reconstruction utilizes already developed glacial chronologies and maps.

Spatiotemporal reconstruction and transmission dynamics during the 2016-17 H5N8 highly pathogenic avian influenza epidemic in Italy.

SummaryEffective control of avian diseases in domestic populations requires understanding of the transmission dynamics facilitating viral emergence and spread. In 2016–17, Italy experienced a significant avian influenza epidemic caused by a highly pathogenic A(H5N8) virus, which affected domestic premises housing around 2.7 million birds, primarily in the north‐eastern regions with the highest density of poultry farms (Lombardy, Emilia‐Romagna and Veneto). We perform integrated analyses of genetic, spatiotemporal and host data within a Bayesian phylogenetic framework. Using continuous and discrete phylogeography, we estimate the locations of movements responsible for the spread and persistence of the epidemic. The information derived from these analyses on rates of transmission between regions through time can be used to assess the success of control measures. Using an approach based on phylogenetic–temporal distances between domestic cases, we infer the presence of cryptic wild bird‐mediated transmission, information that can be used to complement existing epidemiological methods for distinguishing transmission within the domestic population from incursions across the wildlife–domestic interface, a common challenge in veterinary epidemiology. Spatiotemporal reconstruction of the epidemic reveals a highly skewed distribution of virus movements with a high proportion of shorter distance local movements interspersed with occasional long‐distance dispersal events associated with wild birds. We also show how such inference be used to identify possible instances of human‐mediated movements where distances between phylogenetically linked domestic cases are unusually high.

Spatio-temporal silhouette sequence reconstruction for gait recognition against occlusion

Gait-based features provide the potential for a subject to be recognized even from a low-resolution image sequence, and they can be captured at a distance without the subject’s cooperation. Person recognition using gait-based features (gait recognition) is a promising real-life application. However, several body parts of the subjects are often occluded because of beams, pillars, cars and trees, or another walking person. Therefore, gait-based features are not applicable to approaches that require an unoccluded gait image sequence. Occlusion handling is a challenging but important issue for gait recognition. In this paper, we propose silhouette sequence reconstruction from an occluded sequence (sVideo) based on a conditional deep generative adversarial network (GAN). From the reconstructed sequence, we estimate the gait cycle and extract the gait features from a one gait cycle image sequence. To regularize the training of the proposed generative network, we use adversarial loss based on triplet hinge loss incorporating Wasserstein GAN (WGAN-hinge). To the best of our knowledge, WGAN-hinge is the first adversarial loss that supervises the generator network during training by incorporating pairwise similarity ranking information. The proposed approach was evaluated on multiple challenging occlusion patterns. The experimental results demonstrate that the proposed approach outperforms the existing state-of-the-art benchmarks.

Robust single-shot acquisition of high resolution whole brain ASL images by combining time-dependent 2D CAPIRINHA sampling with spatio-temporal TGV reconstruction

For ASL perfusion imaging in clinical settings the current guidelines recommends pseudo-continuous arterial spin labeling with segmented 3D readout. This combination achieves the best signal to noise ratio with reasonable resolution but is prone to motion artifacts due to the segmented readout. Motion robust single-shot 3D acquisitions suffer from image blurring due to the T2 decay of the sampled signals during the long readout. To tackle this problem, we propose an accelerated 3D-GRASE sequence with a time-dependent 2D-CAIPIRINHA sampling pattern. This has several advantages: First, the single-shot echo trains are shortened by the acceleration factor; Second, the temporal incoherence between measurements is increased; And third, the coil sensitivity maps can be estimated directly from the averaged k-space data. To obtain improved perfusion images from the undersampled time series, we developed a variational image reconstruction approach employing spatio-temporal total-generalized-variation (TGV) regularization. The proposed ASL-TGV method reduced the total acquisition time, improved the motion robustness of 3D ASL data, and the image quality of the cerebral blood flow (CBF) maps compared to those by a standard segmented approach. An evaluation was performed on 5 healthy subjects including intentional movement for 2 subjects. Single-shot whole brain CBF-maps with high resolution 3.1 × 3.1 × 3 mm and image quality can be acquired in 1min 46sec. Additionally high quality CBF- and arterial transit time (ATT) -maps from single-shot multi-post-labeling delay (PLD) data can be gained with the proposed method. This method may improve the robustness of 3D ASL in clinical settings, and may be applied for perfusion fMRI.

The First Complete Genome Sequences of Hepatitis C Virus Subtype 2b from Latin America: Molecular Characterization and Phylogeographic Analysis.

The hepatitis C virus (HCV) has remarkable genetic diversity and exists as eight genotypes (1 to 8) with distinct geographic distributions. No complete genome sequence of HCV subtype 2b (HCV-2b) is available from Latin American countries, and the factors underlying its emergence and spread within the continent remain unknown. The present study was conducted to determine the first full-length genomic sequences of HCV-2b isolates from Latin America and reconstruct the spatial and temporal diversification of this subtype in Brazil. Nearly complete HCV-2b genomes isolated from two Brazilian patients were obtained by direct sequencing of long PCR fragments and analyzed together with reference sequences using the Bayesian coalescent and phylogeographic framework approaches. The two HCV-2b genomes were 9318 nucleotides (nt) in length (nt 37–9354). Interestingly, the long RT-PCR technique was able to detect co-circulation of viral variants that contained an in-frame deletion of 2022 nt encompassing E1, E2, and p7 proteins. Spatiotemporal reconstruction analyses suggest that HCV-2b had a single introduction in Brazil during the early 1980s, displaying an epidemic history characterized by a low and virtually constant population size until the present time. These results coincide with epidemiological data in Brazil and may explain the low national prevalence of this subtype.

Genetic structure of the Chagas disease vector Triatoma infestans (Hemiptera: Reduviidae) based on nuclear and mitochondrial DNA sequences

AbstractIn the present study, we analysed the genetic structure of Triatoma infestans populations with a phylogeographical approach using sequences of the mitochondrial NADH dehydrogenase subunit 5 (ND5) and the nuclear elongation factor-1 alpha (EF-1α) genes of bugs obtained from Argentina and Bolivia. Spatially circumscribed haplogroups were distinguished from the ND5 gene sequences, one distributed exclusively to the south of the studied area and, in agreement with the results from the EF-1α gene, one haplogroup limited to Bolivia and another to Morajú located in the Chaco region of Argentina. In both the ND5 and EF-1α networks, the most widespread haplogroup or allele group showed a star-like topology, which is compatible with a recent demographic expansion. The asymmetric historical gene flow detected from a population of the Chaco region towards Bolivia and the spatiotemporal phylogeographical reconstruction of lineage dispersal would support the hypothesis that postulates the Chaco biogeographical region as the area of origin for the species. However, additional studies with a broader sampling in the Andean region are needed to define with certainty whether the origin of T. infestans is Chacoan or Andean.

Are shifts in species distribution triggered by climate change? A swordfish case study

Species shifts due to climate change are being recorded and reported worldwide. However, the accurate estimation and causal attribution of species shifts using spatial distribution indicators, such as the center of gravity, is challenging. This is particularly problematic for commercially exploited marine species with data from research surveys, commercial fisheries or other data collection methods that are not recorded homogeneously over time and space. Here, we propose a new framework to ascertain whether the changes in the spatial distribution of species are due to changes in habitat conditions, fishing activity or other factors. This approach is developed to help elucidate the main drivers of species shifts and it is based upon the comparison of historical trends in species distribution shifts among raw data and modeled: i) fishing effort, ii) population occurrence and abundance, iii) habitat, and iv) spatio-temporal reconstruction of the species distribution. We apply this new methodology to the case study of swordfish populations worldwide. On a global scale, 2 out of 6 stocks of swordfish shifted latitudinally during 1958–2004. Of those two, only the Mediterranean stock was associated with a linear trend change of its habitat. In two other stocks, the latitudinal center of gravity of populations occurrence varies following their habitats’ interannual variability; however, this shift is not linear. We further developed a worldwide habitat suitability model for swordfish and projected its distribution and abundance into the future under the RCP8.5 climate change scenario, the highest greenhouse gas concentration scenario, by the end of the century. Future projections estimate an overall swordfish decrease of 22% in CPUE (catch per unit of effort), with substantial decreases in most tropical areas, and a slight increase in its distribution range limits, both in the north and southern hemispheres.

The sensitivity of dendrogeomorphic approaches to assessing landslide movements

An understanding of past landslide behaviour is crucial for the estimation of future landslide activity. In this respect, methods of absolute dating are frequently used for landslide history assessment. Dendrogeomorphic (tree ring-based) approaches are standard methods for the spatio-temporal reconstruction of landslide activity with annual to even sub-annual resolution and timespans of several centuries (depending on the tree age). Nevertheless, the verification of the effectiveness, sensitivity and precision of these dendrogeomorphic approaches has not been addressed in more detail despite their wide spectrum of limitations. This study makes an assessment of tree ring-based chronologies of landslides based on a comparison with the independent data of past landslide activity from instrumental monitoring. The chronology of past landslide events was created from 528 tree ring series from 132 individuals of Norway spruce (Picea abies (L.) Karst.) growing on a monitored landslide in the Outer Western Carpathians (the Ondřejník Mt.) and was expressed as the yearly variation in the standard event-response index. The landslide was monitored at two sites via technical levelling (since 2007) and an automated wire extensometer (since 2014). The obtained results show a high sensitivity of reaction wood formation to movements on the order of several mm (e.g., the abrupt acceleration of movements in February 2017, as recorded by the extensometer). Moreover, a one-year delay in the growth response to movement occurring in the middle part of the growing season of the previous year was detected. This fact fully supports the introduction of the dendrological year to dendrogeomorphic research. The partial lack of correspondence between tree ring records and data from more distant monitoring sites suggests the need for separate dendrogeomorphic analyses of the individual homogenous parts of landslide areas. Finally, the use of four instead of two increment cores per tree did not provide any extra event years but increased the values of the event-response index of the dated events.

Spatio-Temporal Reconstruction of MODIS NDVI by Regional Land Surface Phenology and Harmonic Analysis of Time-Series

Satellite-derived Normalized Difference Vegetation Index (NDVI) is frequently obstructed by adverse atmospheric components resulting in data gaps in time series. The harmonic analysis of time series (HANTS) algorithm is a widely used technique to reconstruct missing NDVI time series. However, due to restriction of HANTS to act within temporal dimension, its direct application is bound to endure practical problems in spatiotemporal reconstruction due to large data gaps. This study proposes Moving Offset Method (MOM), a novel prefilling method applied on NDVI time series prior to application of HANTS. MOM restores the missing NDVI time series by assuming that it tends to follow a reference pattern of land surface phenology (NDVI ref ). The NDVI ref is prepared by using a recursive search and fill algorithm (SFA) for data availability without null values. It restores null values in NDVI ref at a pixel by using coefficients of linear regression with NDVI ref at another pixel having identical conditions. Finally, the prefilling is prior to application of HANTS. The proposed approach is demonstrated by using MODIS 16-daily time series data for Northeast India and Bhutan region which is covered with frequent seasonal clouds. Besides direct application of HANTS, it is also compared with similar approaches which includes prefilling by inverse distance weighted (IDW) and cubic spline, prior to application of HANTS. The fitting indicators, overall reconstruction error (ORE) and normalized noise related error (NNRE) are found to be best for proposed approach in spatiotemporal comparison. Also, restoration of seasonality trait the NDVI time series better in the proposed approach. This approach is concluded to be an enhancement for HANTS that could be helpful in improving quality of NDVI reconstruction for regions with frequent seasonal obstructions around the globe.

Reconstruction of the spatial and temporal dynamics of hepatitis B virus genotype D in the Americas.

Hepatitis B virus (HBV) genotype D (HBV/D) is globally widespread, and ten subgenotypes (D1 to D10) showing distinct geographic distributions have been described to date. The evolutionary history of HBV/D and its subgenotypes, for which few complete genome sequences are available, in the Americas is not well understood. The main objective of the current study was to determine the full-length genomic sequences of HBV/D isolates from Brazil and frequency, origin and spread of HBV/D subgenotypes in the Americas. Complete HBV/D genomes isolated from 39 Brazilian patients infected with subgenotypes D1 (n = 1), D2 (n = 10), D3 (n = 27), and D4 (n = 1) were sequenced and analyzed together with reference sequences using the Bayesian coalescent and phylogeographic framework. A search for HBV/D sequences available in GenBank revealed 209 complete and 926 partial genomes from American countries (Argentina, Brazil, Canada, Chile, Colombia, Cuba, Haiti, Martinique, Mexico, USA and Venezuela), with the major circulating subgenotypes identified as D1 (26%), D2 (17%), D3 (36%), D4 (21%), and D7 (1%) within the continent. The detailed evolutionary history of HBV/D in the Americas was investigated by using different evolutionary time scales. Spatiotemporal reconstruction analyses using short-term substitution rates suggested times of the most recent common ancestor for the American HBV/D subgenotypes coincident with mass migratory movements to Americas during the 19th and 20th centuries. In particular, significant linkages between Argentina and Syria (D1), Brazil and Central/Eastern Europe (D2), USA and India (D2), and Brazil and Southern Europe (D3) were estimated, consistent with historical and epidemiological data.

Referenced compressed sensing for accurate and fast spatio-temporal signal reconstruction

We address two challenges of applying compressed sensing in a practical application, namely, its poor reconstruction quality and its high computational complexity. Since most signals are not fully sparse in practice, the reconstructed signals from conventional reconstruction methods often suffer from reconstruction artifacts due to the distortion of small coefficients. To improve the reconstruction quality, we introduce referenced compressed sensing (RefCS), a reconstruction method that exploits the spatial and/or temporal redundancy between a pair of signals. We show that using a correlated reference—an arbitrary signal close to the compressed signal—there exists the bound of reconstruction error that depends on the distance between the reference and the signal. By exploiting the correlated reference, RefCS can improve the reconstruction quality by up to 90% in terms of peak signal-to-noise ratio. Moreover, it is possible to reduce the computational complexity of the proposed RefCS using the least squares method. The least squares reconstruction results can be obtained with quality comparable to that of iterative algorithms by employing the correlated reference. Using the least squares method improves the reconstruction time by a factor in the range of 9 to 5.4 × 10^4 according to our experiments.

Comparative studies of compact kHz and MHz driven low pressure plasmas by emission and laser spectroscopy

The temporal evolution of a low pressure argon plasma driven by a combination of radio frequency and kilohertz frequency power sources was characterized by phase resolved optical emission and laser absorption spectroscopy. The compact, low pressure plasma was formed in a hybrid surface/jet geometry and powered by a high voltage power supply operating at 31 kHz and by a lower voltage RF supply operating at 13.56 MHz. An accurate evaluation of the 1s state density dynamics was performed by means of laser absorption measurements of the 1s5 and 1s4 sublevels. The emission spectra were recorded with a submicrosecond temporal resolution and evaluated using an extended Corona model. In comparison with the modeling results, the phase dependent ratio of different Ar(2p) → Ar(1s) emission lines was used to determine temporal profiles of electron temperature and relative electron density. The results were compared with the results from time averaged emission measurements by performing an identical analysis. Strong spatial and temporal variations of plasma parameters were observed when the plasma was driven solely by the 31 kHz source, resulting in nonequilibrium conditions for long living states. Inconsistent observations in the reconstructed temporal development of plasma energy and density were further investigated by illustrating full spatiotemporal reconstruction of plasma parameters. These results permit clear identification of strong spatial gradients through the tube.