149 research outputs found
Rapid divergence of ecotypes of an invasive plant
No full textInvasive species demonstrate rapid evolution within a very short period of time allowing one to understand the underlying mechanism(s). Lantana camara, a highly invasive plant of the tropics and subtropics, has expanded its range and successfully established itself almost throughout India. In order to uncover the processes governing the invasion dynamics, 218 individuals from various locations across India were characterized with six microsatellites. By integrating genetic data with niche modelling, we examined the effect of drift and environmental selection on genetic divergence. We found multiple genetic clusters that were non-randomly distributed across space. Spatial autocorrelation revealed a strong fine-scale structure, i.e. isolation by distance. In addition, we obtained evidence of inhibitory effects of selection on gene flow, i.e. isolation by environmental distance. Perhaps, local adaptation in response to selection is offsetting gene flow and causing the populations to diverge. Niche models suggested that temperature and precipitation play a major role in the observed spatial distribution of this plant. Based on a non-random distribution of clusters, unequal gene flow among them and different bioclimatic niche requirements, we concluded that the emergence of ecotypes represented by two genetic clusters is underway. They may be locally adapted to specific climatic conditions, and perhaps at the very early stages of ecological divergence
The Birth of Aus Agriculture in the South-eastern Highlands of India – an Exploratory Synthesis
No full textAway from the Ganges valley, the south-eastern highlands of India is recognized as the region of origin of upland or 'aus' rice. In this narrative, we attempt to reconstruct its origin synthesizing inklings from genetics, prehistory, and anthropology, and to find out the putative paleo-ecological, environmental, and cultural context that provided the necessary impetus to it. Genetically, we uncover a highly diverse phenotypic base with unique alleles hinting at an independent origin of 'aus' perhaps from 'Oryza nivara'. Post-LGM paleo-niche portrays more widely distributed 'O. nivara' as opposed to 'O. rufipogon'; relatively abundant 'O. nivara' could have enabled its preferential exploitation. While a dearth of archaeological study does not illuminate much on this aspect; the agricultural attributes of the ethnic inhabitants of the area, e.g., dry rice cultivation with the hoe and the axe, reveal a striking similarity with 'aus' or upland rice cultivation. Furthermore, comparative analyses with other historical anecdotes suggest that upland rice seems to be born as an adaptive landscape management by pre-agriculturist society. It was developed through a broader plant-people-landscape interaction, where rice or its ancestors were grown for subsistence with other crops as a Neolithic proto-agricultural package; in this case along the hill slopes. Summarizing, the current study casts light on some of the understudied aspects of upland rice agriculture, but it also brings out many open questions inviting future examination
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Efficient approaches in network inference
No full textNetwork based inference is almost ubiquitous in modern machine learning applications. In this dissertation we investigate several such problems motivated by applications in social networks, biological networks, recommendation system, targeted advertising etc. Unavailability of the graph, presence of latent factors, and large network size often make these inference tasks challenging. We develop both generative models and efficient algorithms to solve such problems. We provide analytical guarantees, in terms of accuracy and computation time, for all our algorithms and demonstrate their applicability on many real datasets. This dissertation mainly consists of two parts. In the first part we consider three different problems. We first consider the task of learning the Markov network structure in a discreet graphical model. We develop three fast greedy algorithms to solve this problem which succeeds even in graphs with strong non-neighbor interaction where previous convex optimization based methods fail. Next we consider the problem of learning latent user interests in different topics, using cascades which spread over a network. Our new algorithm infers both user interests and topics in large cascades, better than standard topic modeling algorithms which do not consider the network structure. In the third problem we develop a novel recursive algorithm based on convex relaxation to detect overlapping communities in a graph. The second part of the dissertation develops a mathematical framework to handle different sources of side information and use it to improve inference in networks. However first we demonstrate a much general technique to incorporate variety of side information in estimating a single component of a mixture model e.g. Gaussian mixture model, latent Dirichlet allocation, subspace clustering, and mixed linear regression. We then use a similar technique to solve the problem of identifying a single target community in a graph, using reference nodes or biased node weights as side information. Our algorithms are based on a variant of method of moments, and are much faster and more accurate than other unsupervised and semi-supervised algorithms.Electrical and Computer Engineerin
<i>Syzygium </i>(Myrtaceae): Monographing a taxonomic giant via 22 coordinated regional revisions
No full textSyzygium Gaertn. is the largest woody genus of flowering plants in the world. Unpublished but extensive recent herbarium surveys suggest 1200‒1800 species distributed throughout the Old World tropics and subtropics (Table 1). Until recently, Syzygium exemplified a recurring taxonomic impediment among megadiverse genera, wherein few taxonomists worked on the group in any sustained manner, a majority of the herbarium specimens remained undetermined or misidentified, few if any attempts were made to look at the genus globally, and limited or no molecular studies were available to provide a predictive phylogenetic context of the genus. The situation with Syzygium has slowly begun to change as allied genera have been absorbed into the genus (Biffin et al., 2006; Craven & Biffin, 2010), and predictive phylogenetically-based infrageneric classifications are emerging. Taxonomic outputs on Syzygium also have been increasing across its range with the description of new species, resolution of nomenclatural and typification issues, and some regional revisions being initiated or updated. However, virtually all regional treatments (which some areas lack) need urgent revision because they are severely outdated, have limited molecular sampling and are error-ridden. We are coordinating a genus-wide taxonomic update of Syzygium through a series of 22 regional revisions, including 9 in the Flora Malesiana region (Figure 1). Each treatment will include a phylogenetic framework with species descriptions, type information, synonymy, distributions, ecological notes, and keys. Field images (Figure 2) and/or line drawings will be included with the goal of every species being illustrated. This working group has been formed to encourage a coordinated effort to document this unwieldy taxonomic giant and regional botanists working on the group are encouraged to be involved. A robust taxonomy of the genus is a prerequisite for testing the many complex questions about evolution and ecology that Syzygium could help address.</jats:p
Time-dependent density functional theory for x-ray absorption spectra: Comparing the real-time approach to linear response
No full textWe examine the simulation of x-ray absorption spectra at elemental K-edges using time-dependent density functional theory, in both its conventional linear-response implementation and also its "real-time" formulation. Real-time simulations enable broadband x-ray spectra calculations without the need to invoke frozen occupied orbitals or "core/valence separation", but we find that the spectra are frequently contaminated by transitions to the continuum originating from lower-energy core and semi-core orbitals. This problem becomes acute in triple-zeta basis sets although it is sometimes bypassed serendipitously in lower-quality basis sets. Transitions to the continuum acquire surprisingly large dipole oscillator strengths, leading to spectra that are difficult or impossible to interpret. Meaningful spectra can be recovered by means of a filtering technique that decomposes the spectrum into contributions from individual occupied orbitals, and the same procedure can be used to separate L- and K-edge spectra. Nevertheless, the conventional linear-response approach is significantly more efficient even when hundreds of individual states are needed to reproduce near-edge absorption features, and even when Pade approximants are used to reduce the real-time simulations to less than 2 fs of time propagation. The real-time approach may be useful for examining the validity of core/valence separation, however
In-situ small angle x-ray scattering investigation on nucleation and growth of silica colloids
No full textEffect of cross-linked biodegradable polymers on sustained release of sodium diclofenac-loaded microspheres
No full textThe objective of this study was to formulate an oral sustained release delivery system of sodium diclofenac(DS) based on sodium alginate (SA) as a hydrophilic carrier in combination with chitosan (CH) and sodium carboxymethyl cellulose (SCMC) as drug release modifiers to overcome the drug-related adverse effects and to improve bioavailability. Microspheres of DS were prepared using an easy method of ionotropic gelation. The prepared beads were evaluated for mean particle size, entrapment efficiency, swelling capacity, erosion and in-vitro drug release. They were also subjected to various studies such as Fourier Transform Infra-Red Spectroscopy (FTIR) for drug polymer compatibility, Scanning Electron Microscopy for surface morphology, X-ray Powder Diffraction Analysis (XRD) and Differential Scanning Calorimetric Analysis (DSC) to determine the physical state of the drug in the beads. The addition of SCMC during the preparation of polymeric beads resulted in lower drug loading and prolonged release of the DS. The release profile of batches F5 and F6 showed a maximum drug release of 96.97 ± 0.356% after 8 h, in which drug polymer ratio was decreased. The microspheres of sodium diclofenac with the polymers were formulated successfully. Analysis of the release profiles showed that the data corresponds to the diffusion-controlled mechanism as suggested by Higuchi
Fundamentals of Cache Aided Wireless Networks
No full textCaching at the network edge has emerged as a viable solution for alleviating the severe capacity crunch in content-centric next generation 5G wireless networks by leveraging localized content storage and delivery. Caching generally works in two phases namely (i) storage phase where parts of popular content is pre-fetched and stored in caches at the network edge during time of low network load and (ii) delivery phase where content is distributed to users at times of high network load by leveraging the locally stored content. Cache-aided networks therefore have the potential to leverage storage at the network edge to increase bandwidth efficiency. In this dissertation we ask the following question - What are the theoretical and practical guarantees offered by cache aided networks for reliable content distribution while minimizing transmission rates and increasing network efficiency?
We furnish an answer to this question by identifying fundamental Shannon-type limits for cache aided systems. To this end, we first consider a cache-aided network where the cache storage phase is assisted by a central server and users can demand multiple files at each transmission interval. To service these demands, we consider two delivery models - (i) centralized content delivery where demands are serviced by the central server; and (ii) device-to-device-assisted distributed delivery where demands are satisfied by leveraging the collective content of user caches. For such cache aided networks, we develop a new technique for characterizing information theoretic lower bounds on the fundamental storage-rate trade-off. Furthermore, using the new lower bounds, we establish the optimal storage-rate trade-off to within a constant multiplicative gap and show that, for the case of multiple demands per user, treating each set of demands independently is order-optimal. To address the concerns of privacy in multicast content delivery over such cache-aided networks, we introduce the problem of caching with secure delivery. We propose schemes which achieve information theoretic security in cache-aided networks and show that the achievable rate is within a constant multiplicative factor of the information theoretic optimal secure rate. We then extend our theoretical analysis to the wireless domain by studying a cloud and cache-aided wireless network from a perspective of low-latency content distribution. To this end, we define a new performance metric namely normalized delivery time, or NDT, which captures the worst-case delivery latency. We propose achievable schemes with an aim to minimize the NDT and derive information theoretic lower bounds which show that the proposed schemes achieve optimality to within a constant multiplicative factor of 2 for all values of problem parameters. Finally, we consider the problem of caching and content distribution in a multi-small-cell heterogeneous network from a reinforcement learning perspective for the case when the popularity of content is unknown. We propose a novel topology-aware learning-aided collaborative caching algorithm and show that collaboration among multiple small cells for cache-aided content delivery outperforms local caching in most network topologies of practical interest. The results presented in this dissertation show definitively that cache-aided systems help in appreciable increase of network efficiency and are a viable solution for the ever evolving capacity demands in the wireless communications landscape.Ph. D.Caching at the network edge has emerged as a viable solution for alleviating the severe capacity crunch in content-centric next generation 5G wireless networks by leveraging localized content storage and delivery. Caching generally works in two phases namely (i) storage phase where parts of popular content is pre-fetched and stored in caches at the network edge during time of low network load and (ii) delivery phase where content is distributed to users at times of high network load by leveraging the locally stored content. Cache-aided networks therefore have the potential to leverage storage at the network edge to increase bandwidth efficiency. In this dissertation we study cache-aided systems from an information theoretic perspective and identify fundamental Shannontype limits for such systems. The results presented in this dissertation show definitively that cacheaided systems help in appreciable increase of network efficiency and are a viable solution for the ever evolving capacity demands in the wireless communications landscape
Shattering or not shattering: that is the question in domestication of rice (Oryza sativa L.)
No full textGuest Editorial Special Issue on Sensing and Machine Learning for Automotive Perception
No full textGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Signal Processing System
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