Effect of Volume Fraction and Fiber Distribution on Stress Transfer in a Stochastic Framework of Continuous Fiber Composite: A Micromechanical Study

In fiber Reinforced Composites (FRC) fiber breakage is a common phenomenon resulting in stress concentration. This high stress gets transfer in the vicinity of the breakage which is quantified by Stress Transfer Coefficient (STC). In this paper, an attempt is made to check the effect of fiber volume fraction and the distribution of the fibers on STC and ineffective length. The fiber volume fraction is changed considering three cases: 1) by changing the number of fibers, 2) by changing the dimension of the Represntative Volume Element (RVE) and 3) by changing the fiber radius. Cases with change in dimension of RVE and change in fiber radius, periodic and semi-random arrangents of fibers are considered. From the analysis of 200 RVE's for each volume fraction in random and semi-random arrangements, it is observed that the distribution of STC does not follow any standard distribution, even if the fiber arrangement follows the normal distribution. The fiber cross-sectional dimension plays a critical role in regaining the broken fiber strength. The periodic arrangement of fibers can be said to be beneficial over the random arrangement considering the stress transfer from the broken fiber

A FUZZY GOAL PROGRAMMING APPROACH FOR SOLVING MULTI-OBJECTIVE SUPPLY CHAIN NETWORK PROBLEMS WITH PARETO-DISTRIBUTED RANDOM VARIABLES

Uncertainty is unavoidable and addressing the same is inevitable. That everything is available at our doorstep is due to a well-managed modern global supply chain, which takes place despite its efficiency and effectiveness being threatened by various sources of uncertainty originating from the demand side, supply side, manufacturing process, and planning and control systems. This paper addresses the demand- and supply-rooted uncertainty. In order to cope with uncertainty within the constrained multi-objective supply chain network, this paper develops a fuzzy goal programming methodology, with solution procedures. The probabilistic fuzzy goal multi-objective supply chain network (PFG-MOSCN) problem is thus formulated and then solved by three different approaches, namely, simple additive goal programming approach, weighted goal programming approach, and pre-emptive goal programming approach, to obtain the optimal solution. The proposed work links fuzziness in transportation cost and delivery time with randomness in demand and supply parameters. The results may prove to be important for operational managers in manufacturing units, interested in optimizing transportation costs and delivery time, and implicitly, in optimizing profits. A numerical example is provided to illustrate the proposed model

TCP Libra: Exploring RTT-Fairness for TCP

The majority of Internet users rely on the Transmission Control Protocol (TCP) to download large multimedia files from remote servers (e.g. P2P file sharing). TCP has been advertised as a fair-share protocol. However, when session round-trip-times (RTTs) radically differ from each other, the share (of the bottleneck link) may be anything but fair. This motivates us to explore a new TCP, TCP Libra, that guarantees fair sharing regardless of RTT. TCP Libra is source only based and thus easy to deploy. Via analytic modeling and simulations we show that TCP Libra achieves fairness while maintaining efficiency and friendliness to TCP New Reno. A comparison with other TCP versions that have been reported as RTT-fair in the literature is also carried out

Seedless Pattern Growth of Quasi-Aligned ZnO Nanorod Arrays on Cover Glass Substrates in Solution

A hybrid technique for the selective growth of ZnO nanorod arrays on wanted areas of thin cover glass substrates was developed without the use of seed layer of ZnO. This method utilizes electron-beam lithography for pattern transfer on seedless substrate, followed by solution method for the bottom-up growth of ZnO nanorod arrays on the patterned substrates. The arrays of highly crystalline ZnO nanorods having diameter of 60 ± 10 nm and length of 750 ± 50 nm were selectively grown on different shape patterns and exhibited a remarkable uniformity in terms of diameter, length, and density. The room temperature cathodluminescence measurements showed a strong ultraviolet emission at 381 nm and broad visible emission at 585–610 nm were observed in the spectrum

Co-immunization efficacy of recombinant antigens against Rhipicephalus microplus and Hyalomma anatolicum tick infestations

This article belongs to the Collection Advances in Tick Research.The immunoprophylactic management of ticks is the most effective option to control tick infestations and counter spread the acaricide resistance problem worldwide. Several researchers reported an inconsistent efficacy of the single antigen-based immunization of hosts against different tick species. In the present study, to develop a multi-target immunization protocol, proteins from Rhipicephalus microplus BM86 and Hyalomma anatolicum subolesin (SUB) and tropomyosin (TPM) were targeted to evaluate the cross-protective potential. The sequence identities of the BM86, SUB, and TPM coding genes amongst Indian tick isolates of targeted species were 95.6–99.8%, 98.7–99.6%, and 98.9–99.9%, respectively, while at the predicted amino acid level, the identities were 93.2 to 99.5, 97.6 to 99.4, and 98.2 to 99.3%. The targeted genes were expressed in the eukaryotic expression system, pKLAC2-Kluyveromyces lactis, and 100 µg each of purified recombinant protein (Bm86-89 kDa, SUB-21 kDa, and TPM-36 kDa) mixed with adjuvant was injected individually through the intramuscular route at different sites of the body on days 0, 30, and 60 to immunize cross-bred cattle. Post-immunization, a statistically significant (p < 0.001) antibody response (IgG, IgG1, and IgG2) in comparison to the control, starting from 15 to 140 days, against each antigen was recorded. Following multi-antigen immunization, the animals were challenged twice with the larvae of R. microplus and H. anatolicum and theadults of H. anatolicum, and a significant vaccine efficacy of 87.2% and 86.2% against H. anatolicum larvae and adults, respectively, and 86.7% against R. microplus was obtained. The current study provides significant support to develop a multi-antigen vaccine against cattle tick species.The authors are grateful to the Indian Council of Agricultural Research (ICAR), New Delhi, India for funding through the National Agricultural Science Fund (Grant number NASF/ABA-6015/2016-17/357 and NFBSFARA/BSA-4004/2013-14. The APC is funded by authors.Peer reviewe

Teamwork delivers biotechnology products to Indian small-holder crop-livestock producers: Pearl millet hybrid “HHB 67 Improved” enters seed delivery pipeline

HHB 67, released in 1990 by CCS Haryana Agricultural University, is one such single-cross pearl millet hybrid. HHB 67 is highly popular because of its extra-early maturity (it needs less than 65 days from sowing to grain maturity) and is now grown on over 500 000 ha in Haryana and Rajasthan, India. Recent surveys have indicated that this hybrid is starting to succumb to downy mildew (DM; caused by the pseudo-fungus Sclerospora graminicola), showing up to 30% incidence in farmers' fields. By rapidly adopting hybrid "HHB 67 Improved", farmers in Haryana and Rajasthan can avoid grain production losses of Rs36 crores (US$8 million) which would be expected in the first year of a major DM outbreak on the original HHB 67

Ontology-guided data preparation for discovering genotype-phenotype relationships

International audienceComplexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic frame to data and because they benefit from the progress of semantic web technologies, bio-ontologies should be considered for playing a key role in the KDD process. In the frame of a case study relative to the search of genotype-phenotype relationships, we demonstrate the capability of bio-ontologies to guide data selection during the preparation step of the KDD process. We propose three scenarios to illustrate how domain knowledge can be taken into account in order to select or aggregate data to mine, and consequently how it can facilitate result interpretation at the end of the process

Data Sciences Technology for Homeland Security Information Management and Knowledge Discovery

The Department of Homeland Security (DHS) has vast amounts of data available, but its ultimate value cannot be realized without powerful technologies for knowledge discovery to enable better decision making by analysts. Past evidence has shown that terrorist activities leave detectable footprints, but these footprints generally have not been discovered until the opportunity for maximum benefit has passed. The challenge faced by the DHS is to discover the money transfers, border crossings, and other activities in advance of an attack and use that information to identify potential threats and vulnerabilities. The data to be analyzed by DHS comes from many sources ranging from news feeds, to raw sensors, to intelligence reports, and more. The amount of data is staggering; some estimates place the number of entities to be processed at 1015. The uses for the data are varied as well, including entity tracking over space and time, identifying complex and evolving relationships between entities, and identifying organization structure, to name a few. Because they are ideal for representing relationship and linkage information, semantic graphs have emerged as a key technology for fusing and organizing DHS data. A semantic graph organizes relational data by using nodes to represent entities and edges to connect related entities. Hidden relationships in the data are then uncovered by examining the structure and properties of the semantic graph