Potent and selective bicyclic lactam inhibitors of thrombin: Part 2: P1 modifications

The synthesis and antithrombotic activity of a series of nonpeptide bicyclic thrombin inhibitors is described. We have explored the SAR with modifications to the P1 site. The introduction of arginine mimetics at the P1 site led to potent and selective thrombin inhibitors.     

A case of clofazimine enteropathy

A case of clofazimine enteropathy is described. A young male received clofazimine 200 mg daily for four years. He was admitted in a pigmented, emaciated state with abdominal pain, diarrhoea and weight loss. At laparotomy his abdominal organs were stained with dark brown-black pigment due to heavy infiltration with clofazimine crystals. Despite withdrawal of clofazimine his symptoms failed to settle. He developed oedema and hypoalbuminaemia. He died following a cerebral infarction.     

Facile Deposition of Silver Nanoparticles on Photonic Cellulose Nanocrystals Films: A Study on Solvent Stability and Post Antibacterial Activity

Cellulose nanocrystals (CNCs) incorporated with silver nanoparticles (AgNPs) photonic films have drawn considerable attention due to their plasmonic chiroptical activity. However, the exploitation of some fundamental properties for practical use such as the affinity analysis of metal nanoparticles attached to the surface of photonic films according to the solvent compatibility and antibacterial activity under physical conditions has yet not been studied. Hence, a facile process of in situ deposition of AgNPs into the chiral structure of CNC films is proposed. CNC photonic films, cross-linked by glutaraldehyde are prepared. This interaction generated the solvents-stable photonic film with a considerable amount of unreacted aldehyde functional groups that facilitates the reduction of Ag salt to AgNPs. The formed AgNPs in the photonic films show excellent stability over immersion in various polar and non-polar solvents. The post-solvent treated photonic films display excellent contact-based antibacterial behavior against gram-negative Escherichia coli.     

Random-effects regression analysis of correlated grouped-time survival data

Random-effects regression modelling is proposed for analysis of correlated grouped-time survival data. Two analysis approaches are considered. The first treats survival time as an ordinal outcome, which is either right-censored or not. The second approach treats survival time as a set of dichotomous indicators of whether the event occurred for time periods up to the period of the event or censor. For either approach both proportional hazards and proportional odds versions of the random-effects model are developed, while partial proportional hazards and odds generalizations are described for the latter approach. For estimation, a full-information maximum marginal likelihood solution is implemented using numerical quadrature to integrate over the distribution of multiple random effects. The quadrature solution allows some flexibility in the choice of distributions for the random effects; both normal and rectangular distributions are considered in this article. An analysis of a dataset where students are clustered within schools is used to illustrate features of random-effects analysis of clustered grouped-time survival data.     

Infrared spectroscopic investigation of tannins

Infrared spectroscopy is suggested as a diagnostic method for the characterisation and qualitative estimation of the two classes of tannins. Gallic acid, tannic acid and chebulinic acid have been taken as model compounds for the hydrolysable and catechin for the condensed tannins. The former class is marked by the presence of strong absorption maxima at 1710 – 35 cm^?1. The two classes have characteristic pattern of absorption, from which it is possible to characterise the particular type of tannin.     

Kigelia pinnata Seed Oil – A Moderate Source of Vernolic Acid

Vernolic acid represents 22.3% of the constituent fatty acids of the speed oil of an additional hitherto unexamined species of Bignoniaceae Kigelia pinnata. Its identification is based on comparative informations from thin-layer chromatography, infrared analysis, gas liquid chromatography and nuclear magnetic resonance spectroscopy with that of reference sample of Vernonia anthelmintica seed oil. The other fatty acids in this oil are: 14:0 (0.4), 16:0 (25.4), 18:0(0.9), 18:1 (8.9) and 18:2 (42.0%). K. pinnata is the first species of Bignoniaceae to be reported to contain vernolic acid in moderate amount.     

Isolation and characterization of cellulose nanowhiskers from Acacia caesia plant

Acacia caesia (L.) Willd (soap bark) fiber is an abundant natural resource, that is rich in cellulose. The study reports the effective utilization of underutilized Acacia caesia fiber for the isolation of nanocellulose whiskers. The nanocellulose whiskers were isolated successfully from Acacia caesia fibers by following alkali, bleaching, and sulfuric acid treatment. The obtained nanocellulose whiskers were carefully investigated for its chemical composition, structure, morphology, crystallinity, and thermal stability. The chemical composition and Fourier transform infrared spectra of nanocellulose whiskers showed the elimination of the non-cellulosic parts present in the raw Acacia caesia fibers. The X-ray diffraction analysis showed an upsurge in the crystallinity of the cellulose fibers after the chemical treatments. The isolation of nanocellulose whiskers from Acacia caesia raw fiber was confirmed by electron microscopy analysis. The thermogravimetric analysis showed remarkably high char residue for the nanocellulose whiskers compared to raw fibers. Based on the properties of nanocellulose whiskers, it can be concluded that the nanocellulose whiskers produced from Acacia caesia raw fibers are potential reinforcing material for developing high-performance green composites.     

Parameter estimation for five- and seven-parameter photovoltaic electrical models using evolutionary algorithms

Equivalent electric circuit modeling of PV devices is widely used to predict PV electrical performance. The first task in using the model to calculate the electrical characteristics of a PV device is to find the model parameters which represent the PV device. In the present work, parameter estimation for the model parameter using various evolutionary algorithms is presented and compared. The constraint set on the estimation process is that only the data directly available in module datasheets can be used for estimating the parameters. The electrical model accuracy using the estimated parameters is then compared to several electrical models reported in literature for various PV cell technologies.     

A formal mapping-based approach for distributed schedule coordination on projects

Construction projects involve a large number of participants with overlapping scope of work. Coordination of their activities is usually an iterative manual task undertaken by a general contractor that is often unaware of the detailed constraints of other participants. Project schedules play a key role in this coordination and form the backbone of almost all current approaches to process coordination. However, no single schedule represents the perspective of all participants involved in a project. Rather, each participant keeps in some manner a schedule for its own activities, resulting in multiple schedules that need to be coordinated. The current literature does not support simultaneous reasoning across multiple distributed, overlapping schedules. This paper introduces constructs to formalize the integration of participants’ overlapping schedules that represent the same project tasks, but use a different set breakdown structures and level of detail. Implementation of these constructs allows linking of the master schedule to the other participants’ schedules thereby representing the perspectives of all project participants. This integrated perspective facilitates initial schedule coordination and allows rapid identification of schedule conflicts in response to any schedule changes.     

Graph attention-based collaborative filtering for user-specific recommender system using knowledge graph and deep neural networks

Knowledge and Information Systems - Collaborative filtering suffers from the issues of data sparsity and cold start. Due to which recommendation models that only rely on the user–item...