Some progress on the chemistry of natural bioactive terpenoids form Chinese medicinal plants

(1) Pseudolaric acids - Novel diterpenes, Pseudolaric acid A, B, C and D were isolated from Pseudolarix kaempferi Gorden (pinaceae). Their structures were assigned by spectroscopic data and chemical correlations. In the contineous studies, the absolute configurations, the conformations in the solutions, the framentation mechanisms of MS and assigments of all NMR spectral signals were also reported. They showed the antifungal and cytotoxic activities. (2) Daphnane diterpenes - In the further studies on the plants of Thymelaeaceae, besides 10 known diterpenes, 16 new daphnane diterpenes were isolated from Daphne genkwa, D. tangutica, D. giraldii, Wikstroemie chamaedaphne. They showed the antifertilities activities. (3) Tripterygium diterpenes 14 new diterpenes were isolated from Triperygium wilfordii, T. regeli and T. hypoglaucum. Some of them showed the antitumor activities. The CD spectra showed that A/B ring of all compoundshave trans configuration as same as tripdiolide and triptolide determined by X-ray diffraction (4) Pregnane glycosides from Marsdenia koi - Two new pregnane glycosides marsdenikoiside A and marsdenikoiside B which can terminate the early pregnancy were isolated from Marsdeia koi. Their structures were elucidated by hydrolysis and spectroscopic methods.

Learning to live together: an exploration and analysis of managing cultural diversity in ten early childhood development centres in South Africa

This study explores how South African Early Childhood Development (ECD) Practitioners and families meet the needs of the increasing number of children from diverse cultural backgrounds in their care. Research participants were identified through ten ECD centres located in two urban communities in the Eastern and Western Cape Provinces of South Africa. The values and attitudes held by Practitioners and families vis-à-vis cultural diversity was investigated, along with the knowledge and strategies they employ to manage cultural diversity in ECD programmes. The intercultural education model provides the necessary tools to address the challenges identified.

Learning-induced plasticity in human audition: Objects, time, and space.

The human auditory system is comprised of specialized but interacting anatomic and functional pathways encoding object, spatial, and temporal information. We review how learning-induced plasticity manifests along these pathways and to what extent there are common mechanisms subserving such plasticity. A first series of experiments establishes a temporal hierarchy along which sounds of objects are discriminated along basic to fine-grained categorical boundaries and learned representations. A widespread network of temporal and (pre)frontal brain regions contributes to object discrimination via recursive processing. Learning-induced plasticity typically manifested as repetition suppression within a common set of brain regions. A second series considered how the temporal sequence of sound sources is represented. We show that lateralized responsiveness during the initial encoding phase of pairs of auditory spatial stimuli is critical for their accurate ordered perception. Finally, we consider how spatial representations are formed and modified through training-induced learning. A population-based model of spatial processing is supported wherein temporal and parietal structures interact in the encoding of relative and absolute spatial information over the initial ∼300ms post-stimulus onset. Collectively, these data provide insights into the functional organization of human audition and open directions for new developments in targeted diagnostic and neurorehabilitation strategies.

Investigation of Postmortem Gases: A Forensic Imaging and Analytical Chemistry Approach

Background: Distinguishing postmortem gas accumulations in the body due to natural decomposition and other phenomena such as gas embolism can prove a difficult task using purely Multi-Detector Computed Tomography (MDCT). The Radiological Alteration Index (RAI) was created with the intention to be able to identify bodies undergoing the putrefaction process based on the quantity of gas detected within the body. The flaw in this approach is the inability to absolutely determine putrefaction as the origin of gas volumes in cases of moderate alteration. The aim of the current study is to identify percentage compositions of O2, N2, CO2 and the presence of gases such as H2 and H2S within these sampling sites in order to resolve this complication. Materials and methods: All cases investigated in our University Center of Legal Medicine are undergoing a Post-Mortem Computed Tomography (PMCT)-scan before external examination or autopsy as a routine investigation. In the obtained images, areas of gas were characterized as 0, I, II or III based on the amount of gas present according to the RAI (1). The criteria for these characterizations were dependent of the site of gas, for example thoracic and abdominal cavities were graded as I (1 - 3cm gas), II (3 - 5cm gas) and III (>5cm gas). Cases showing gaseous sites with grade II or III were selected for this study. The sampling was performed under CT-guidance to target the regions to be punctured. Luer-lock PTFE syringes equipped with a three-way valve and needles were used to sample the gas directly (2). Gaseous samples were then analysed using gas chromatography coupled to a thermal conductivity detector (GC-TCD). The components present in the samples were expressed as a percentage of the overall gas present. Results: Up to now, we have investigated more than 40 cases using our standardized procedure for sampling and analysis of gas. O2, N2 and CO2 were present in most samples. The following distributions were found to correlate to gas origins of gas embolism/scuba diving accidents, trauma and putrefaction: ? Putrefaction → O2 = 1 - 5%; CO2 > 15%; N2 = 10 - 70%; H2 / H2S / CH4 variable presence ? Gas embolism/Scuba diving accidents → O2 and N2= varying percentages; CO2 > 20% ? Trauma → O2 = small percentage; CO2 < 15%; N2 > 65% H2 and H2S indicated levels of putrefaction along with methane which can also gauge environmental conditions or conditions of body storage/burial. Many cases showing large RAI values (advanced alteration) did reveal a radiological diagnosis which was in concordance with the interpretation of the gas composition. However, in certain cases (gas embolism, scuba divers) radiological interpretation was not possible and only chemical gas analysis was found to lead to the correct diagnosis, meaning that it provided complementary information to the radiological diagnosis. Conclusion: Investigation of postmortem gases is a useful tool to determine origin of gas generation which can aid the diagnosis of the cause of death. Levels of gas can provide information on stage of putrefaction and help to perform essential medico-legal diagnosis such as vital gas embolism.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Desarrollo de un sistema de e-Learning para Nintendo DS

El proyecto trata de crear un software que dinámicamente nos proporcione exámenes o pruebas dependiendo de nuestro nivel de conocimientos actual. Estos exámenes se cargarán a través de un fichero XML configurable, lo que nos permitirá poner a prueba nuestros conocimientos en el tema que deseemos. El software se desarrollará en Nintendo DS, para aprovechar las prestaciones que nos ofrece de serie: doble pantalla, pantalla táctil, portabilidad.

Interoperability issues between learning object repositories and metadata harvesters

In this paper we describe an open learning object repository on Statistics based on DSpace which contains true learning objects, that is, exercises, equations, data sets, etc. This repository is part of a large project intended to promote the use of learning object repositories as part of the learning process in virtual learning environments. This involves the creation of a new user interface that provides users with additional services such as resource rating, commenting and so. Both aspects make traditional metadata schemes such as Dublin Core to be inadequate, as there are resources with no title or author, for instance, as those fields are not used by learners to browse and search for learning resources in the repository. Therefore, exporting OAI-PMH compliant records using OAI-DC is not possible, thus limiting the visibility of the learning objects in the repository outside the institution. We propose an architecture based on ontologies and the use of extended metadata records for both storing and refactoring such descriptions.

The Role of model uncertainty and learning in the U.S. postwar policy response to oil prices

This paper studies optimal monetary policy in a framework that explicitly accounts for policymakers' uncertainty about the channels of transmission of oil prices into the economy. More specfically, I examine the robust response to the real price of oil that US monetary authorities would have been recommended to implement in the period 1970 2009; had they used the approach proposed by Cogley and Sargent (2005b) to incorporate model uncertainty and learning into policy decisions. In this context, I investigate the extent to which regulator' changing beliefs over different models of the economy play a role in the policy selection process. The main conclusion of this work is that, in the specific environment under analysis, one of the underlying models dominates the optimal interest rate response to oil prices. This result persists even when alternative assumptions on the model's priors change the pattern of the relative posterior probabilities, and can thus be attributed to the presence of model uncertainty itself.

Advanced mapping of environmental data: Geostatistics, Machine Learning and Bayesian Maximum Entropy

This book combines geostatistics and global mapping systems to present an up-to-the-minute study of environmental data. Featuring numerous case studies, the reference covers model dependent (geostatistics) and data driven (machine learning algorithms) analysis techniques such as risk mapping, conditional stochastic simulations, descriptions of spatial uncertainty and variability, artificial neural networks (ANN) for spatial data, Bayesian maximum entropy (BME), and more.

Cooperative learning: learning to cooperate, cooperating to learn

This research project is an attempt to give arguments in favour of using cooperative learning activities in FL classrooms as an effective approach to learning. The arguments offered are presented from two different perspectives: the first one is based on the empirical study of three students working together to achieve a common goal. The second one is a compilation of the trainee teacher's experiences during her practicum periods in a high school regarding group work. This part is illustrated by some examples that emphasize that cooperative learning can facilitate learning, promote socialisation and increase students' self-esteem