scholarly journals Determination of Motivation of 5th Grade Students Living in Rural and Urban Environments towards Science Learning and their Attitudes towards Science-technology Course

2016 ◽  
Vol 4 (7) ◽  
Author(s):  
İsmail Kenar ◽  
Mücahit Köse ◽  
Halil İbrahim Demir
Keyword(s):  
Science Learning ◽  
Urban Environments ◽  
Science Technology ◽  
Rural And Urban ◽  
Attitudes Towards Science ◽  
5Th Grade ◽  
Technology Course

scholarly journals Soil and nutrient losses in erosion gullies at different degrees of restoration

2010 ◽  
Vol 34 (3) ◽  
pp. 945-954 ◽  
Author(s):  
Roriz Luciano Machado ◽  
Alexander Silva de Resende ◽  
Eduardo Francia Carneiro Campello ◽  
José Arimathéa Oliveira ◽  
Avílio Antônio Franco
Keyword(s):  
Low Cost ◽  
Soil Classification ◽  
Urban Environments ◽  
Nutrient Loss ◽  
Data Sets ◽  
Nutrient Losses ◽  
Sediment Grain Size ◽  
Rural And Urban ◽  
Soil Sediment

The most advanced stage of water erosion, the gully, represents severe problems in different contexts, both in rural and urban environments. In the search for a stabilization of the process in a viable manner it is of utmost importance to assess the efficiency of evaluation methodologies. For this purpose, the efficiency of low-cost conservation practices were tested for the reduction of soil and nutrient losses caused by erosion from gullies in Pinheiral, state of Rio de Janeiro. The following areas were studied: gully recovered by means of physical and biological strategies; gullies in recovering stage, by means of physical strategies only, and gullies under no restoration treatment. During the summer of 2005/2006, the following data sets were collected for this study: soil classification of each of the eroded gully areas; planimetric and altimetric survey; determination of rain erosivity indexes; determination of amount of soil sediment; sediment grain size characteristics; natural amounts of nutrients Ca, Mg, K and P, as well as total C and N concentrations. The results for the three first measurements were 52.5, 20.5, and 29.0 Mg in the sediments from the gully without intervention, and of 1.0, 1.7 and 1.8 Mg from the gully with physical interventions, indicating an average reduction of 95 %. The fully recovered gully produced no sediment during the period. The data of total nutrient loss from the three gullies under investigation showed reductions of 98 % for the recovering gully, and 99 % for the fully recovered one. As for the loss of nutrients, the data indicate a nutrient loss of 1,811 kg from for the non-treated gully. The use of physical and biological interventions made it possible to reduce overall nutrient loss by more than 96 %, over the entire rainy season, as compared to the non-treated gully. Results show that the methods used were effective in reducing soil and nutrient losses from gullies.

Development of analytical thinking ability and attitudes towards science learning of grade-11 students through science technology engineering and mathematics (STEM education) in the study of stoichiometry

2016 ◽  
Vol 17 (4) ◽  
pp. 842-861 ◽  
Author(s):  
Patcharee Chonkaew ◽  
Boonnak Sukhummek ◽  
Chatree Faikhamta
Keyword(s):  
Stem Education ◽  
Confidence Level ◽  
Science Learning ◽  
Problem Based Learning ◽  
Science Technology ◽  
Analytical Thinking ◽  
Thinking Ability ◽  
Attitudes Towards Science ◽  
And Mathematics ◽  
Grade 11

The purpose of this study was to investigate the analytical thinking abilities and attitudes towards science learning of grade-11 students through science, technology, engineering, and mathematics (STEM) education integrated with a problem-based learning in the study of stoichiometry. The research tools consisted of a pre- and post-analytical thinking ability test, a science learning attitude test, classroom observations, student reflective journals, and semi-structured interviews. The findings indicated that STEM learning activities based on problem-based learning successfully developed analytical thinking abilities and attitudes towards science learning. Consequently, the students realized how important theories are, and were able to integrate their knowledge from various fields to solve problems and to create new innovations. About 80% of the students showed higher analytical thinking ability scores above the prescribed criterion of 70% of the full score. After learning, the scores of the students were higher than those before learning at a confidence level of 0.01. The attitudes towards science learning were higher than those before learning at a confidence level of 0.01. The successful activities of STEM started with offering knowledge to students through an inquiry-based process until they could construct the knowledge on their own. After that, the teacher initiated a problem situation and allowed each group of students to create a useful product adopted from the experimental results via integrating STEM knowledge to modify their creative works.

scholarly journals Gut Microbiota Dynamics in Natural Populations of Pintomyia evansi under Experimental Infection with Leishmania infantum

2021 ◽  
Vol 9 (6) ◽  
pp. 1214
Author(s):  
Rafael José Vivero ◽  
Victor Alfonso Castañeda-Monsalve ◽  
Luis Roberto Romero ◽  
Gregory D. Hurst ◽  
Gloria Cadavid-Restrepo ◽  
...  
Keyword(s):  
Gut Microbiota ◽  
Leishmania Infantum ◽  
Natural Populations ◽  
Illumina Miseq ◽  
Urban Environments ◽  
High Load ◽  
Leishmania Infection ◽  
Experimental Conditions ◽  
Rural And Urban ◽  
Negative Effect

Pintomyia evansi is recognized by its vectorial competence in the transmission of parasites that cause fatal visceral leishmaniasis in rural and urban environments of the Caribbean coast of Colombia. The effect on and the variation of the gut microbiota in female P. evansi infected with Leishmania infantum were evaluated under experimental conditions using 16S rRNA Illumina MiSeq sequencing. In the coinfection assay with L. infantum, 96.8% of the midgut microbial population was composed mainly of Proteobacteria (71.0%), followed by Cyanobacteria (20.4%), Actinobacteria (2.7%), and Firmicutes (2.7%). In insect controls (uninfected with L. infantum) that were treated or not with antibiotics, Ralstonia was reported to have high relative abundance (55.1–64.8%), in contrast to guts with a high load of infection from L. infantum (23.4–35.9%). ASVs that moderately increased in guts infected with Leishmania were Bacillus and Aeromonas. Kruskal–Wallis nonparametric variance statistical inference showed statistically significant intergroup differences in the guts of P. evansi infected and uninfected with L. infantum (p < 0.05), suggesting that some individuals of the microbiota could induce or restrict Leishmania infection. This assay also showed a negative effect of the antibiotic treatment and L. infantum infection on the gut microbiota diversity. Endosymbionts, such as Microsporidia infections (<2%), were more often associated with guts without Leishmania infection, whereas Arsenophonus was only found in guts with a high load of Leishmania infection and treated with antibiotics. Finally, this is the first report that showed the potential role of intestinal microbiota in natural populations of P. evansi in susceptibility to L. infantum infection.

Damage assessment mapping of rural environments; integration of SAR and Optical data

2021 ◽  
Author(s):  
Shiran Havivi ◽  
Stanley R. Rotman ◽  
Dan G. Blumberg ◽  
Shimrit Maman
Keyword(s):  
Natural Disaster ◽  
Rural Areas ◽  
Urban Areas ◽  
Damage Assessment ◽  
Vegetation Index ◽  
Urban Environments ◽  
Optical Data ◽  
Damage Level ◽  
Rural Environments ◽  
Rural And Urban

&lt;p&gt;The damage caused by a natural disaster in rural areas differs in nature, extent, landscape and in structure, from the damage in urban environments. Previous and current studies focus mainly on mapping damaged structures in urban areas after catastrophe events such as an earthquake or tsunami. Yet, research focusing on the damage level or its distribution in rural areas is absent. In order to apply an emergency response and for effective disaster management, it is necessary to understand and characterize the nature of the damage in each different environment.&amp;#160;&lt;/p&gt;&lt;p&gt;Havivi et al. (2018), published a damage assessment algorithm that makes use of SAR images combined with optical data, for rapid mapping and compiling a damage assessment map following a natural disaster. The affected areas are analyzed using interferometric SAR (InSAR) coherence. To overcome the loss of coherence caused by changes in vegetation, optical images are used to produce a mask by computing the Normalized Difference Vegetation Index (NDVI) and removing the vegetated area from the scene. Due to the differences in geomorphological settings and landuse\landcover between rural and urban settlements, the above algorithm is modified and adjusted by inserting the Modified Normalized Difference Water Index (MNDWI) to better suit rural environments and their unique response after a disaster. MNDWI is used for detection, identification and extraction of waterbodies (such as irrigation canals, streams, rivers, lakes, etc.), allowing their removal which causes lack of coherence at the post stage of the event. Furthermore, it is used as an indicator for highlighting prone regions that might be severely affected pre disaster event. Thresholds are determined for the co-event coherence map (&amp;#8804; 0.5), the NDVI (&amp;#8805; 0.4) and the MNDWI (&amp;#8805; 0), and the three layers are combined into one. Based on the combined map, a damage assessment map is generated.&amp;#160;&lt;/p&gt;&lt;p&gt;As a case study, this algorithm was applied to the areas affected by multi-hazard event, following the Sulawesi earthquake and subsequent tsunami in Palu, Indonesia, which occurred on September 28th, 2018. High-resolution COSMO-SkyMed images pre and post the event, alongside a Sentinel-2 image pre- event are used as inputs. The output damage assessment map provides a quantitative assessment and spatial distribution of the damage in both the rural and urban environments. The results highlight the applicability of the algorithm for a variety of disaster events and sensors. In addition, the results enhance the contribution of the water component to the analysis pre and post the event in rural areas. Thus, while in urban regions the spatial extent of the damage will occur in its proximity to the coastline or the fault, rural regions, even in significant distance will experience extensive damage due secondary hazards as liquefaction processes.&amp;#160; &amp;#160; &amp;#160;&lt;/p&gt;

scholarly journals Bounding the Practical Error of Path Loss Models

2012 ◽  
Vol 2012 ◽  
pp. 1-21 ◽  
Author(s):  
Caleb Phillips ◽  
Douglas Sicker ◽  
Dirk Grunwald
Keyword(s):  
A Priori ◽  
Path Loss ◽  
Urban Environments ◽  
Production Networks ◽  
Modeling Error ◽  
Propagation Models ◽  
Performance Accuracy ◽  
Rural And Urban ◽  
Standard Models ◽  
Loss Models

We seek to provide practical lower bounds on the prediction accuracy of path loss models. We describe and implement 30 propagation models of varying popularity that have been proposed over the last 70 years. Our analysis is performed using a large corpus of measurements collected on production networks operating in the 2.4 GHz ISM, 5.8 GHz UNII, and 900 MHz ISM bands in a diverse set of rural and urban environments. We find that the landscape of path loss models is precarious: typical best-case performance accuracy of these models is on the order of 12–15 dB root mean square error (RMSE) and in practice it can be much worse. Models that can be tuned with measurements and explicit data fitting approaches enable a reduction in RMSE to 8-9 dB. These bounds on modeling error appear to be relatively constant, even in differing environments and at differing frequencies. Based on our findings, we recommend the use of a few well-accepted and well-performing standard models in scenarios wherea prioripredictions are needed and argue for the use of well-validated, measurement-driven methods whenever possible.

scholarly journals Evidence and theory for lower rates of depression in larger US urban areas

2021 ◽  
Vol 118 (31) ◽  
pp. e2022472118
Author(s):  
Andrew J. Stier ◽  
Kathryn E. Schertz ◽  
Nak Won Rim ◽  
Carlos Cardenas-Iniguez ◽  
Benjamin B. Lahey ◽  
...  
Keyword(s):  
Mental Health ◽  
Social Networks ◽  
Social Determinants ◽  
Urban Areas ◽  
Urban Environments ◽  
City Size ◽  
Built Environments ◽  
Rural And Urban ◽  
Us Cities ◽  
Systematic Framework

It is commonly assumed that cities are detrimental to mental health. However, the evidence remains inconsistent and at most, makes the case for differences between rural and urban environments as a whole. Here, we propose a model of depression driven by an individual’s accumulated experience mediated by social networks. The connection between observed systematic variations in socioeconomic networks and built environments with city size provides a link between urbanization and mental health. Surprisingly, this model predicts lower depression rates in larger cities. We confirm this prediction for US cities using four independent datasets. These results are consistent with other behaviors associated with denser socioeconomic networks and suggest that larger cities provide a buffer against depression. This approach introduces a systematic framework for conceptualizing and modeling mental health in complex physical and social networks, producing testable predictions for environmental and social determinants of mental health also applicable to other psychopathologies.

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