Ginger (Kaempferia galanga L) Supplementation to Shorten Broiler Production Period

Consumers increasingly prefer to buy broiler weighted approximately one kg.  In this study broiler chicks were feed with commercial diet, which composed from corn, soybean, fishmeal, rice bran, dicalcium phosphate, vitamins minerals mixture (premix) and palm oil. The diet contained approximately 20.33 % of crude protein and 3100 Kcal/kg of metabolizable energy.  The ginger meal was mixed into the diet according to the treatments i.e P1 (0 %), P2 (0.02%), P3 (0.04 %), P4 (0.08 %) and P5 (0.16 %). The results showed that the total feed intake of P5 (1,808.4 g) and P2 (1,846.5 g) was significantly (P<0.05) less than those of P1 (1,966.5 g). Birds of P5 achieved one kg body weight within 26 days, P2 (27 days) and P3 (27 days) was significantly (P<0.05) less than those compared with birds of P4 (29 hari) and P1 (30 hari). The feed conversion of P5 (1.81) was also better than (P<0.05) that of P1 (1.97), while the Income over Feed and Chick Cost was Rp 1,658.78 (P5); Rp 1,568.06 (P2); Rp 1,426.54 (P3);   Rp 1,280.45 (P1) and Rp 1,195.95 (P4). (Animal Production 8(1): 59-63 (2006) Key Words : Kaempferia galanga L, Broile

Scalable variational Gaussian process classification

Gaussian process classification is a popular method with a number of appealing properties. We show how to scale the model within a variational inducing point framework, outperforming the state of the art on benchmark datasets. Importantly, the variational formulation can be exploited to allow classification in problems with millions of data points, as we demonstrate in experiments.JH was supported by a MRC fellowship, AM and ZG by EPSRC grant EP/I036575/1, and a Google Focussed Research award.This is the final version of the article. It was first available from JMLR via http://jmlr.org/proceedings/papers/v38/hensman15.pd

Latent Topic Text Representation Learning on Statistical Manifolds

The explosive growth of text data requires effective methods to represent and classify these texts. Many text learning methods have been proposed, like statistics-based methods, semantic similarity methods, and deep learning methods. The statistics-based methods focus on comparing the substructure of text, which ignores the semantic similarity between different words. Semantic similarity methods learn a text representation by training word embedding and representing text as the average vector of all words. However, these methods cannot capture the topic diversity of words and texts clearly. Recently, deep learning methods such as CNNs and RNNs have been studied. However, the vanishing gradient problem and time complexity for parameter selection limit their applications. In this paper, we propose a novel and efficient text learning framework, named Latent Topic Text Representation Learning. Our method aims to provide an effective text representation and text measurement with latent topics. With the assumption that words on the same topic follow a Gaussian distribution, texts are represented as a mixture of topics, i.e., a Gaussian mixture model. Our framework is able to effectively measure text distance to perform text categorization tasks by leveraging statistical manifolds. Experimental results on text representation and classification, and topic coherence demonstrate the effectiveness of the proposed method

Effet d'une complémentation azotée sur la pathologie de la trypanosomose animale africaine chez les moutons sahéliens

Effect of a Complementation Nitrogenized on the Pathology of Animal Trypanosomiasis at the Sahelian Sheeps. La méthode thermique pour la détermination de flux de sève et la chambre à pression pour mesurer les potentiels hydriques foliaire et xylémique, ont été utilisées chez l'olivier de table Olea europaea cv Meski pour estimer la conductance hydraulique et la participation élémentaire des 4 branches selon l'orientation et l'exposition aux radiations solaires. Les mesures ont été effectuées du 23-10-2004 au 30-11-2004 dans un verger d'olivier de table et principalement sur deux arbres de la variété la plus commercialisée Meski. Cette étude a permis l'estimation de la conductance globale de la plante ainsi que la contribution de chaque génératrice. Les taux des conductances hydrauliques partielles sont respectivement de 43, 24, 20 et 13% dans les branches est, nord, sud et ouest. Elle a montré l'importance de l'interception lumineuse dans le déterminisme des flux de sève et des potentiels hydriques foliaires dans chaque branche, et par conséquent la liaison avec le mode de taille et la densité de plantation à préconiser

MCMC for variationally sparse Gaussian processes

Gaussian process (GP) models form a core part of probabilistic machine learning. Considerable research effort has been made into attacking three issues with GP models: how to compute efficiently when the number of data is large; how to approximate the posterior when the likelihood is not Gaussian and how to estimate covariance function parameter posteriors. This paper simultaneously addresses these, using a variational approximation to the posterior which is sparse in support of the function but otherwise free-form. The result is a Hybrid Monte-Carlo sampling scheme which allows for a non-Gaussian approximation over the function values and covariance parameters simultaneously, with efficient computations based on inducing-point sparse GPs. Code to replicate each experiment in this paper will be available shortly.JH was funded by an MRC fellowship, AM and ZG by EPSRC grant EP/I036575/1 and a Google Focussed Research award.This is the final version of the article. It first appeared from the Neural Information Processing Systems Foundation via https://papers.nips.cc/paper/5875-mcmc-for-variationally-sparse-gaussian-processe

Late-onset bloodstream infection and perturbed maturation of the gastrointestinal microbiota in premature infants

Late-onset bloodstream infection (LO-BSI) is a common complication of prematurity, and lack of timely diagnosis and treatment can have life-threatening consequences. We sought to identify clinical characteristics and microbial signatures in the gastrointestinal microbiota preceding diagnosis of LO-BSI in premature infants.Daily faecal samples and clinical data were collected over two years from 369 premature neonates (<32 weeks gestation). We analysed samples from 22 neonates who developed LO-BSI and 44 matched control infants. Next-generation sequencing of 16S rRNA gene regions amplified by PCR from total faecal DNA was used to characterise the microbiota of faecal samples preceding diagnosis from infants with LO-BSI and controls. Culture of selected samples was undertaken, and bacterial isolates identified using MALDI-TOF. Antibiograms from bloodstream and faecal isolates were compared to explore strain similarity.From the week prior to diagnosis, infants with LO-BSI had higher proportions of faecal aerobes/facultative anaerobes compared to controls. Risk factors for LO-BSI were identified by multivariate analysis. Enterobacteriaceal sepsis was associated with antecedent multiple lines, low birth weight and a faecal microbiota with prominent Enterobacteriaceae. Staphylococcal sepsis was associated with Staphylococcus OTU faecal over-abundance, and the number of days prior to diagnosis of mechanical ventilation and of the presence of centrally-placed lines. In 12 cases, the antibiogram of the bloodstream isolate matched that of a component of the faecal microbiota in the sample collected closest to diagnosis.The gastrointestinal tract is an important reservoir for LO-BSI organisms, pathogens translocating across the epithelial barrier. LO-BSI is associated with an aberrant microbiota, with abundant staphylococci and Enterobacteriaceae and a failure to mature towards predominance of obligate anaerobes

Crystallisation of Aspirin via Simulated Pulmonary Surfactant Monolayers and Lung-Specific Additives

Pain is a prevalent condition that can have a serious impact upon the socioeconomic function of a population. Numerous methods exist to administer analgesic medication (e.g. aspirin) to the body however inherent drawbacks limit patient acceptability. The inhaled route offers promise to facilitate the administration of medication to the body. Here, we consider the crystallisation behaviour of aspirin, our model therapeutic agent, when in contact with material of relevance to the lung. Thus, our approach aims to better understand the interaction between drug substances and the respiratory tract. Langmuir monolayers composed of a mixed surfactant system were supported on an aqueous subphase containing aspirin (7.5mg/ml). The surfactant film was compressed to either 5mN/m (i.e. inhalation end point) or 50mN/m (i.e. exhalation end point), whilst located within a humid environment for 16 hours. Standard cooling crystallisation procedures were employed to produce control samples. Antisolvent crystallisation in the presence or absence of lung-specific additives was conducted. All samples were analysed via scanning electron microscopy (SEM) and X-ray diffraction (XRD). Drug-surfactant interactions were confirmed via condensed Langmuir isotherms. SEM analysis revealed plate-like morphology. The crystallisation route dictated both the crystal habit and particle size distribution. Dominant reflections were the (100) and (200) aspects. The main modes of interaction were hydrogen bonding, hydrophobic associations and van der Waals forces. Here, we have demonstrated the potential of antisolvent crystallisation with lung-specific additives to achieve control over drug crystal morphology. The approach taken can be applied in respirable formulation engineering

UKRmol+: A suite for modelling electronic processes in molecules interacting with electrons, positrons and photons using the R-matrix method

UKRmol+ is a new implementation of the time-independent UK R-matrix electron–molecule scattering code. Key features of the implementation are the use of quantum chemistry codes such as Molpro to provide target molecular orbitals; the optional use of mixed Gaussian — B-spline basis functions to represent the continuum and improved configuration and Hamiltonian generation. The code is described, and examples covering electron collisions from a range of targets, positron collisions and photoionization are presented. The codes are freely available as a tarball from Zenodo

Viral video style: A closer look at viral videos on YouTube

Viral videos that gain popularity through the process of Internet sharing are having a profound impact on society. Existing studies on viral videos have only been on small or confidential datasets. We collect by far the largest open benchmark for viral video study called CMU Viral Video Dataset, and share it with researchers from both academia and industry. Having verified existing observations on the dataset, we discover some interesting characteristics of viral videos. Based on our analysis, in the second half of the paper, we propose a model to forecast the future peak day of viral videos. The application of our work is not only important for advertising agencies to plan advertising campaigns and estimate costs, but also for companies to be able to quickly respond to rivals in viral marketing campaigns. The proposed method is unique in that it is the first attempt to incorporate video metadata into the peak day prediction. The empirical results demonstrate that the proposed method outperforms the state-of-the-art methods, with statistically significant differences. Copyright 2014 ACM

Radio pulsar populations

The goal of this article is to summarize the current state of play in the field of radio pulsar statistics. Simply put, from the observed sample of objects from a variety of surveys with different telescopes, we wish to infer the properties of the underlying sample and to connect these with other astrophysical populations (for example supernova remnants or X-ray binaries). The main problem we need to tackle is the fact that, like many areas of science, the observed populations are often heavily biased by a variety of selection effects. After a review of the main effects relevant to radio pulsars, I discuss techniques to correct for them and summarize some of the most recent results. Perhaps the main point I would like to make in this article is that current models to describe the population are far from complete and often suffer from strong covariances between input parameters. That said, there are a number of very interesting conclusions that can be made concerning the evolution of neutron stars based on current data. While the focus of this review will be on the population of isolated Galactic pulsars, I will also briefly comment on millisecond and binary pulsars as well as the pulsar content of globular clusters and the Magellanic Clouds.Comment: 16 pages, 6 figures, to appear in Proceedings of ICREA Workshop on The High-Energy Emission from Pulsars and their Systems, Sant Cugat, Spain, 2010 April 12-16 (Springer