Explore the vast range of titles available.

Self-efficacy is described as an individual’s beliefs about their abilities to complete an action. It is a part of the social cognitive theory in the chemistry learning process. self-efficacy consists of six aspects, namely the choice of activities, effort, perseverance, learning, achievement and strategy orientation. The objective of this study was to develop an instrument of chemistry student virtual Laboratory self-efficacy (CSVL-SE) in a virtual laboratory within the chemical equilibrium topic. This research used research and development (R&D) method. The data was obtained through a self-efficacy questionnaire. The expert confirmed the content validity with 26 items that had been administered to 60 students in senior high school. Rasch Model used to analyse the data that met the unidimensionality, item fit, difficulty or ability estimation, reliability, and information function. The findings showed that 26 items match into the Rasch Model with reliability person and reliability item of 0.84 and 0.97. So that, this instrument is appropriate to collect the data.

This study aims to analyse the knowledge and atitude of disaster preparedness student who live around the Mount Merapi area in the face of natural disaster of volcanic eruptions. The research method used descriptive reseaerch using 56 students as respondents. The instruments of this study used tests and quesionnaires. Data analysisi techniques were performed using quantitatif percentages. The results showed that students in the area around Mount Merapi had good knowledge about knowing danger signs of a volcano eruption by 29% and had a disaster preparedness preparedness category of 59%. This research can be used as a development foundation to help reduce the risk of volcanic eruptions.

The aim of this study was to examine the differences of students' cognitive learning outcomes on chemical equilibrium topic through the Science Technology Society (STS) learning approach. Design of this study was quasi-experimental. Specifically, posttest only group design was adopted. The number of sample in this study are 60 students 11th grade. Selection of the sample conducted with a purposive sampling technique. The experimental group was taught by the STS approach, while the control group was scientific approach. The instrument for data collection was chemistry achievement multiple choice questions. Instrument test shows 23 out of 30 questions created were valid. The reliability value obtained was 0.73. Data was collected using the test in the form of score, and analyzed by the t-test. This research concluded that students who were taught Science Technology Society (STS) approaches have better cognitive learning outcomes than the control group. These results suggest the implication of the STS approach can be used as a learning approach to improve students' cognitive learning outcomes.

Scientific literacy was the ability to solve everyday problems and provide concrete evidence in scientific resolution. This research aimed to analyse junior high school students' scientific literacy about effort and simple aircraft in everyday life. This research was included in descriptive quantitative would be using test questions. Test results will be analysed to measure students' scientific literacy skills. The subjects of research were 8th-grade students at schools of medium quality. The research population was all 8-grade students, where all classes were homogeneous and had the same average ability. The sample was chosen because there are no superior classes and academic abilities possessed by heterogeneous students (high, medium, and low). The sampling technique used a purposive sampling technique. The instrument used to measure students' scientific literacy was a scientific literacy test that matched the indicators of scientific literacy. The result of the analysis obtained from each aspect assessed namely identifying scientific issues was of 19.69% included in the very poor category, explaining that scientific phenomena were 32.19% included in the moderate category, and interpreting scientific data and evidence was 33.59% included in the moderate category. These results indicated that the literacy ability of students falls into the poor category.

The aim of the study was to identify the content of total phenolic and flavonoids, and to test the antioxidant activity of leaves extract of Dendrophthoe falcata hemiparasite on Melia azedarach plants. The research method was carried out by extracting dry powder from the leaves of D. falcata with ethanol. Ethanol extract was partitioned using consecutive n-hexane, chloroform, and ethyl acetate solvents. Each fraction was then analyzed for the content of total phenolic and total flavonoids by spectroscopic methods. The method for testing antioxidant activity using 2,2-diphenyl-1-picrylhydrazyl (DPPH) by in vitro. The results showed that leaves of D. falcata were rich in phenolic compounds and flavonoid. Furthermore, in the antioxidant test showed ethyl acetate fraction had the highest activity, with IC50 6.66 ± 0.11 μg/ml. This study shows that D. falcata leaves have potential as natural antioxidants.

Selected endophytic fungi have been report to be inulin degraders to produce fructose or other oligosaccharides. In this study, the Aspergillus sp. producing inulinase were isolated from selected plant species at Serdang area in Malaysia. Fungal isolates were screened solely based on inulin degrading enzymes production and two isolates named Asf1 and Onf1 were selected as the best inulinase enzyme producers. Genomic DNA of these two isolates were extracted and amplified by polymerase chain reaction (PCR). A 1,341 bp DNA fragment containing inulinase gene was successfully amplified from Asf1 fungal isolate and was named as inu2 gene in this study. Based on the morphological characteristics, rDNA and neighbour-joining phylogenetic analysis, Asf1 fungal isolate could display closely-related to the genus of Aspergillus. The complete sequence designated Asf1 Inu2 gene was successfully obtained via rapid-amplification of cDNA ends-polymerase chain reaction (RACE-PCR). A 2.3 kb DNA fragment encoding endoinulinase, inu2 , from Asf1 fungal isolate includes an open reading frame of 1,552 bp with calculated molecular weight of 55,954.1 Da and signal peptide sequence of 23 amino acids. The deduced amino acid sequence of the Asf1 inu2 displayed 97, 96, 69 and 22% identities to that of A. ficuum inu2, A. niger inuB, P. purpurogenum and K. marxianus , respectively. Phylogenetic analysis showed that fungal endo- and exo-inulinases have indepently evolved with the respective hydrolytic activities toward terminal and internal β-(2 → 1)-fructofuranosidic linkages in inulin.

In The Lancet, Theo Vos and colleagues4 present a new analysis-the Global Burden of Disease Study 2013 (GBD 2013). They estimated, at global, regional, and national levels, the incidence, prevalence, and years lived with disability (YLDs) for 301 diseases and injuries, using new data and improved methods that are clearly presented-important in improving the transparency of global health data and research methods.5,6

Machine learning expands on existing statistical techniques [6], utilising methods that are not based on a priori assumptions about the distribution of the data, and can find patterns in the data that can in turn be used to formulate hypotheses and hypothesis tests. [...]whilst machine learning models are more difficult to interpret, they can incorporate many more variables and are generalizable across a much broader array of data types, and can produce results in more complex situations [9]. Pathology – detection of lymph node metastases in breast cancer (s37) Prediction of outcomes in colorectal cancer (s38) Dermatology – identification of benign and malignant tumors (s39), identification of fungal infection (s40), classification of skin cancer (s41) Predicting of survival in non-small cell lung cancer (s42) Ophthalmology – identification of diabetic retinopathy (s43), grading of macular degeneration (s44) Prediction of hospitalization due to heart disease (s45) Cardiology – diagnosis of acute coronary syndrome (s46), identification of heart failure status through remote patient monitoring (s47) Prediction of primary care utilization (s48) Radiology – mammography (s49), diagnosis of pneumonia from chest x-ray [10] Prediction of sepsis in the intensive care unit, emergency department and on the hospital floor (s50) Electronic health record analysis: [...]the potential impact of machine learning should redouble motivation behind these initiatives. The fear of wholesale displacement of health workforce by AI is overstated, but where fear is warranted is in considering the opportunity cost of not embracing AI, of continuing business as usual with piecemeal implementation of AI that does not realize its potential for transformation of health systems. 1 Wellframe Inc., Boston, Massachusetts, USA 2 Department of Electrical Engineering and Computer Science, Computer Science and Artificial Intelligence Laboratory, Massachussetts Institute of Technology, Cambridge, Massachusetts, USA 3 Department of Global Health and Population, Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts, USA 4 Department of Global Health and Social Medicine, Harvard Medical School, Harvard University, Boston, Massachusetts, USA

In 2003, Turkey embarked on ambitious health system reform to overcome major inequities in health outcomes and to protect all citizens against financial risk. Within 10 years, it had achieved universal health coverage and notable improvements in outcomes and equity. In 2003, Turkey embarked on ambitious health system reform to overcome major inequities in health outcomes and to protect all citizens against financial risk. Within 10 years, it had achieved universal health coverage and notable improvements in outcomes and equity. Health insurance was introduced in Turkey in 1945, at first covering blue-collar workers and later other groups. From 1960 onward, Turkey's 5-year development plans included universal health coverage as an objective; a new constitution in 1982 guaranteed rights to health insurance and health services; and a 1987 Basic Law on Health aimed to operationalize these rights. But the law wasn't . . .