Hardware synthesis from DDL description

The details of digital systems can be conveniently input into the design automation system by means of hardware description language (HDL). The computer aided design and test (CADAT) system at NASA MSFC is used for the LSI design. The digital design language (DDL) was selected as HDL for the CADAT System. DDL translator output can be used for the hardware implementation of the digital design. Problems of selecting the standard cells from the CADAT standard cell library to realize the logic implied by the DDL description of the system are addressed

A Generative Model For Zero Shot Learning Using Conditional Variational Autoencoders

Zero shot learning in Image Classification refers to the setting where images from some novel classes are absent in the training data but other information such as natural language descriptions or attribute vectors of the classes are available. This setting is important in the real world since one may not be able to obtain images of all the possible classes at training. While previous approaches have tried to model the relationship between the class attribute space and the image space via some kind of a transfer function in order to model the image space correspondingly to an unseen class, we take a different approach and try to generate the samples from the given attributes, using a conditional variational autoencoder, and use the generated samples for classification of the unseen classes. By extensive testing on four benchmark datasets, we show that our model outperforms the state of the art, particularly in the more realistic generalized setting, where the training classes can also appear at the test time along with the novel classes

APPLICATION OF IPOM OEA BATATA STARCH MUCILAGE AS SUSPENDING AGENT IN OSELTAMIVIR SUSPENSION

Objective: The objective of the study was to search for a cheap and effective natural raw material that can serve as an alternative suspending agent in the formulation of oseltamivir suspension. The phytochemical and the physicochemical properties of the mucilage of Ipomoea batata starch were studied. Methods: The suspending properties of mucilage extract of I. batata starch was evaluated comparatively with that of acacia, xanthum gum and sodium alginate using model formulations at concentrations of 0.75, 1.5and 3.5% w/v. The Prepared suspensions were evaluated by studying different parameters like pH, sedimentation volume, redispersibility, Flow rate (F), viscosity, degree of flocculation, effect, effect of temperature and stability studies. Results: The results showed the presence of flavonoids, saponin, protein, carbohydrate and reducing sugars. The rheological properties of suspension showed that As the concentration of suspending agent increased viscosity also get increased which reduces the sedimentation and contributes to the stability of suspension. Increase in viscosity avoids the particle aggregation so particles remain in a flocculated state. While an increase in temperature did not significantly increased the viscosity of suspension. The order of stability of suspension in terms of sedimentation profile ranked thus: OF3 (3%w/v IBSM)>OF12 (3%w/v SA)>OF6 (3%w/v AG)>OF9 (3%w/v XG)>B (5%w/v potato starch). Conclusion: These results indicate that mucilage from I. batata starch in oseltamivir suspension has low sedimentation rate, medium viscosity and easily dispersible and can therefore serve as suspending agent in formulations of suspensions of sparingly soluble drugs

Agricultural and Finance Intervention Increased Dietary Intake and Weight of Children Living in HIV-Affected Households in Western Kenya.

We tested whether a multisectoral household agricultural and finance intervention increased the dietary intake and improved the nutritional status of HIV-affected children. Two hospitals in rural Kenya were randomly assigned to be either the intervention or the control arm. The intervention comprised a human-powered water pump, microfinance loan for farm commodities, and training in sustainable farming practices and financial management. In each arm, 100 children (0-59 mo of age) were enrolled from households with HIV-infected adults 18-49 y old. Children were assessed beginning in April 2012 and every 3 mo for 1 y for dietary intake and anthropometry. Children in the intervention arm had a larger increase in weight (β: 0.025 kg/mo, P = 0.030), overall frequency of food consumption (β: 0.610 times · wk-1 · mo-1, P = 0.048), and intakes of staples (β: 0.222, P = 0.024), fruits and vegetables (β: 0.425, P = 0.005), meat (β: 0.074, P < 0.001), and fat (β: 0.057, P = 0.041). Livelihood interventions have potential to improve the nutrition of HIV-affected children. This trial was registered at clinicaltrials.gov as NCT01548599

Partnering in a Haze: Interdependence Misspecification and Firm Performance in Strategic Alliances

We examine the implications for firm performance of managers having only a partial understanding of the true nature of their inter-firm interdependence. While operating with such ex-ante uncertainty regarding inter-firm interdependency is common when selecting an approach to governing an alliance relationship, the literature offers limited guidance as to the performance implications of such “misspecifications.” We employ an agent-based simulation to model inter-firm decision making in a context where firms have either under- or over-specified views of their inter-firm interdependencies. Consistent with intuition, firm performance declines with interdependence misspecifications. We find, however, interesting variation in this effect across alternate governance modes and across levels of actual interdependency. We also find that interdependence misspecifications have differing effects on exploration and coordination, leading to tradeoffs between performance and other alliance objectives

Prediction of viral microRNA precursors based on human microRNA precursor sequence and structural features

MicroRNAs (small ~22 nucleotide long non-coding endogenous RNAs) have recently attracted immense attention as critical regulators of gene expression in multi-cellular eukaryotes, especially in humans. Recent studies have proved that viruses also express microRNAs, which are thought to contribute to the intricate mechanisms of host-pathogen interactions. Computational predictions have greatly accelerated the discovery of microRNAs. However, most of these widely used tools are dependent on structural features and sequence conservation which limits their use in discovering novel virus expressed microRNAs and non-conserved eukaryotic microRNAs. In this work an efficient prediction method is developed based on the hypothesis that sequence and structure features which discriminate between host microRNA precursor hairpins and pseudo microRNAs are shared by viral microRNA as they depend on host machinery for the processing of microRNA precursors. The proposed method has been found to be more efficient than recently reported ab-initio methods for predicting viral microRNAs and microRNAs expressed by mammals