Pelestarian Lingkungan Hidup: suatu Kajian Berdasarkan Pendidikan Kependudukan Danlingkungan Hidup (Pklh) di Beberapa Sekolah Dasar

The objective of this research aimed to know about environment conservation in connection with the educational program of population and environment (PKLH) in elementary school (SD), in which or especially located around the Tondano lake, Minahasa, North Sulawesi. The qualitative-descriptive approach was conducted on, during February 2014 at 8 schools. Its focused to headmasters, teachers, students, and then continued by observation of schools and its environment. By using interview and participant-observation techniques, researcher take an active role on the learning activities and direct interaction with students in the classroom. After that continuing to search and observing students activities after and out school. The result of this research shows that PKLH was conducted in SD by using integrative approach, and we find that students get more information and knowledge and have an attitude and proper behavior rationally and responsibly according to their ability and educational level

Biomedical word sense disambiguation with word embeddings

There is a growing need for automatic extraction of information and knowledge from the increasing amount of biomedical and clinical data produced, namely in textual form. Natural language processing comes in this direction, helping in tasks such as information extraction and information retrieval. Word sense disambiguation is an important part of this process, being responsible for assigning the proper concept to an ambiguous term. In this paper, we present results from machine learning and knowledge-based algorithms applied to biomedical word sense disambiguation. For the supervised machine learning algorithms we used word embeddings, calculated from the full MEDLINE literature database, as global features and compare the results to the use of local unigram and bigram features. For the knowledge-based method we represented the textual definitions of biomedical concepts from the UMLS database as word embedding vectors, and combined this with concept associations derived from the MeSH term co-occurrences. Both the machine learning and the knowledge-based results indicate that word embeddings are informative and improve the biomedical word disambiguation accuracy. Applied to the reference MSH WSD data set, our knowledge-based approach achieves 85.1% disambiguation accuracy, which is higher than some previously proposed approaches that do not use machine-learning strategies.publishe

The effect of word sense disambiguation accuracy on literature based discovery

Background The volume of research published in the biomedical domain has increasingly lead to researchers focussing on specific areas of interest and connections between findings being missed. Literature based discovery (LBD) attempts to address this problem by searching for previously unnoticed connections between published information (also known as “hidden knowledge”). A common approach is to identify hidden knowledge via shared linking terms. However, biomedical documents are highly ambiguous which can lead LBD systems to over generate hidden knowledge by hypothesising connections through different meanings of linking terms. Word Sense Disambiguation (WSD) aims to resolve ambiguities in text by identifying the meaning of ambiguous terms. This study explores the effect of WSD accuracy on LBD performance. Methods An existing LBD system is employed and four approaches to WSD of biomedical documents integrated with it. The accuracy of each WSD approach is determined by comparing its output against a standard benchmark. Evaluation of the LBD output is carried out using timeslicing approach, where hidden knowledge is generated from articles published prior to a certain cutoff date and a gold standard extracted from publications after the cutoff date. Results WSD accuracy varies depending on the approach used. The connection between the performance of the LBD and WSD systems are analysed to reveal a correlation between WSD accuracy and LBD performance. Conclusion This study reveals that LBD performance is sensitive to WSD accuracy. It is therefore concluded that WSD has the potential to improve the output of LBD systems by reducing the amount of spurious hidden knowledge that is generated. It is also suggested that further improvements in WSD accuracy have the potential to improve LBD accuracy

Minimal Flavour Violation with Strong Higgs Dynamics

We develop a variant of the Minimal Flavour Violation ansatz for the case of a strongly interacting heavy-Higgs boson sector. The tower of effective operators differs from that for a Higgs system in the linear regime, and the new operators obtained at leading order include a CP-odd one. We investigate the impact of these operators on Delta F=1 and Delta F=2 observables, demonstrating that the non-linear scenario may have an interesting impact on the anomalies in present data.Comment: 35 pages, 4 figures; version accepted for publication on JHE

Training adults and children with an autism spectrum disorder to be compliant with a clinical dental assessment using a TEACCH-based approach

The specific neuropsychological and sensory profile found in persons with autism spectrum disorders complicate dental procedures and as a result of this, most are treated under general anesthesia or unnecessary sedation. The main goal of the present study was to evaluate the effectiveness of a short treatment and education of autistic and related communication-handicapped children-based intervention program (five sessions) to facilitate a 10-component oral assessment in children (n = 38, aged 4¿9 years) and adults (n = 34, aged 19¿41) with autism spectrum disorder (with or without associated intellectual disability). The assessment ranges from entering into the examination room to the evaluation of the dental occlusion. There were statistically significant differences in the number of components reached and in compliance before and after the training program

Findings of the WMT 2021 Biomedical Translation Shared Task: Summaries of Animal Experiments as New Test Set

In the sixth edition of the WMT Biomedical Task, we addressed a total of eight language pairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian, and English/Basque. Further, our tests were composed of three types of textual test sets. New to this year, we released a test set of summaries of animal experiments, in addition to the test sets of scientific abstracts and terminologies. We received a total of 107 submissions from 15 teams from 6 countries