Development And Morphology Of Stelar Components In The Stems Of Some Members Of The Leguminosae And Rosaceae

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141585/1/ajb209994.pd

Chemoenzymatic Labeling of Proteins for Imaging in Bacterial Cells

Reliable methods to determine the subcellular localization of bacterial proteins are needed for the study of prokaryotic cell biology. We describe here a simple and general technique for imaging of bacterial proteins in situ by fluorescence microscopy. The method uses the eukaryotic enzyme N-myristoyltransferase to modify the N-terminus of the protein of interest with an azido fatty acid. Subsequent strain-promoted azide–alkyne cycloaddition allows conjugation of dyes and imaging of tagged proteins by confocal fluorescence microscopy. We demonstrate the method by labeling the chemotaxis proteins Tar and CheA and the cell division proteins FtsZ and FtsA in Escherichia coli. We observe distinct spatial patterns for each of these proteins in both fixed and live cells. The method should prove broadly useful for protein imaging in bacteria

In situ approach for rapid characterization to aid on farm conservation of coconut germplasm - A case study of two ecotypes from West coast of India

Characterization and evaluation of coconut germplasm have conventionally been undertaken in ex situ gene banks, which take a minimum duration of fifteen years. On the other hand, utilization of coconut populations in situ can effectively reduce the time required for characterization of the populations. Hence, a concept to make a paradigm shift in the existing approach of coconut germplasm characterization is advocated in this study with a view to broaden the conservation base and facilitate inclusion of identified diverse ecotypes. The methodology has been applied to identify, locate and characterize two tall coconut ecotypes viz., Bedakam and Kuttiyadi, from northern Kerala. Agronomic traits, viz., higher number of nuts per palm, higher copra content and better performance under marginal management conditions along with adaptation to the environment, were the major reasons for preference of these ecotypes among the farmers. Comparison of the two ecotypes revealed that the traits, trunk girth, length of internode, number of leaves, number of bunches with nuts, number of nuts, shell weight, husked fruit weight and fruit weight were higher in Kuttiyadi than in Bedakam ecotype. On the other hand, number of leaf scars per meter, length of inflorescence, fruit breadth, husk weight, nut cavity volume and copra weight were higher in Bedakam compared to Kuttiyadi ecotype. Relevance, utility and importance of the study are discussed from the perspective of effective utilization of the coconut diversity in situ and their possible further use in coconut improvement efforts through conservation strategies

Wireless sensor networks for in-situ image validation for water and nutrient management

Water and Nitrogen (N) are critical inputs for crop production. Remote sensing data collected from multiple scales, including ground-based, aerial, and satellite, can be used for the formulation of an efficient and cost effective algorithm for the detection of N and water stress. Formulation and validation of such techniques require continuous acquisition of ground based spectral data over the canopy enabling field measurements to coincide exactly with aerial and satellite observations. In this context, a wireless sensor in situ network was developed and this paper describes the results of the first phase of the experiment along with the details of sensor development and instrumentation set up. The sensor network was established based on different spatial sampling strategies and each sensor collected spectral data in seven narrow wavebands (470, 550, 670, 700, 720, 750, 790 nm) critical for monitoring crop growth. Spectral measurements recorded at required intervals (up to 30 seconds) were relayed through a multi-hop wireless network to a base computer at the field site. These data were then accessed by the remote sensing centre computing system through broad band internet. Comparison of the data from the WSN and an industry standard ground based hyperspectral radiometer indicated that there were no significant differences in the spectral measurements for all the wavebands except for 790nm. Combining sensor and wireless technologies provides a robust means of aerial and satellite data calibration and an enhanced understanding of issues of variations in the scale for the effective water and nutrient management in wheat.<br /

Design space exploration and optimization of path oblivious RAM in secure processors

Keeping user data private is a huge problem both in cloud computing and computation outsourcing. One paradigm to achieve data privacy is to use tamper-resistant processors, inside which users' private data is decrypted and computed upon. These processors need to interact with untrusted external memory. Even if we encrypt all data that leaves the trusted processor, however, the address sequence that goes off-chip may still leak information. To prevent this address leakage, the security community has proposed ORAM (Oblivious RAM). ORAM has mainly been explored in server/file settings which assume a vastly different computation model than secure processors. Not surprisingly, naïvely applying ORAM to a secure processor setting incurs large performance overheads. In this paper, a recent proposal called Path ORAM is studied. We demonstrate techniques to make Path ORAM practical in a secure processor setting. We introduce background eviction schemes to prevent Path ORAM failure and allow for a performance-driven design space exploration. We propose a concept called super blocks to further improve Path ORAM's performance, and also show an efficient integrity verification scheme for Path ORAM. With our optimizations, Path ORAM overhead drops by 41.8%, and SPEC benchmark execution time improves by 52.4% in relation to a baseline configuration. Our work can be used to improve the security level of previous secure processors.National Science Foundation (U.S.). Graduate Research Fellowship Program (Grant 1122374)American Society for Engineering Education. National Defense Science and Engineering Graduate FellowshipUnited States. Defense Advanced Research Projects Agency (Clean-slate design of Resilient, Adaptive, Secure Hosts Contract N66001-10-2-4089

Sub-logarithmic Distributed Oblivious RAM with Small Block Size

Oblivious RAM (ORAM) is a cryptographic primitive that allows a client to securely execute RAM programs over data that is stored in an untrusted server. Distributed Oblivious RAM is a variant of ORAM, where the data is stored in $m>1$ servers. Extensive research over the last few decades have succeeded to reduce the bandwidth overhead of ORAM schemes, both in the single-server and the multi-server setting, from $O(\sqrt{N})$ to $O(1)$. However, all known protocols that achieve a sub-logarithmic overhead either require heavy server-side computation (e.g. homomorphic encryption), or a large block size of at least $\Omega(\log^3 N)$. In this paper, we present a family of distributed ORAM constructions that follow the hierarchical approach of Goldreich and Ostrovsky [GO96]. We enhance known techniques, and develop new ones, to take better advantage of the existence of multiple servers. By plugging efficient known hashing schemes in our constructions, we get the following results: 1. For any $m\geq 2$, we show an $m$-server ORAM scheme with $O(\log N/\log\log N)$ overhead, and block size $\Omega(\log^2 N)$. This scheme is private even against an $(m-1)$-server collusion. 2. A 3-server ORAM construction with $O(\omega(1)\log N/\log\log N)$ overhead and a block size almost logarithmic, i.e. $\Omega(\log^{1+\epsilon}N)$. We also investigate a model where the servers are allowed to perform a linear amount of light local computations, and show that constant overhead is achievable in this model, through a simple four-server ORAM protocol