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Fig 6 -
No full textSentinel-1 interferograms and coherence maps for North Selangor: a) VV polarisation from 2/7/2017 to 17/7/2017; b) VH polarisation from 2/7/2017 to 17/7/2017; c) VV polarisation from 14/8/2018 to 14/8/2018; d) the VH polarisation from 14/8/2018 to 14/8/2018. Base map provided by OpenStreetMap®. OpenStreetMap® is open data, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). OpenStreetMap® is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/.</p
Photographs illustrating common land cover types and field conditions at north Selangor.
No full text(a) secondary forest, (b) burned peatland with dense grass and shrubs, (c) rice paddy agriculture and (d) oil palm plantation. (Photo credits: MJL).</p
North Selangor reserve boundary and peatland extent located within Selangor, Peninsular Malaysia, SE Asia.
No full textBase map provided by OpenStreetMap®. OpenStreetMap® is open data, licensed under the Open Data Commons Open Database License (ODbL) by the OpenStreetMap Foundation (OSMF). OpenStreetMap® is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/.</p
Baseline characteristics and univariate analysis of the study population.
No full textBaseline characteristics and univariate analysis of the study population.</p
Structural equation model estimation results across European welfare state regimes.
No full textStructural equation model estimation results across European welfare state regimes.</p
Structural equation model estimation results (as percentages).
No full textStructural equation model estimation results (as percentages).</p
Human participants research checklist.
No full textThe values that people hold are linked to their economic performance. These links can be either direct or indirect, operating through moderating variables such as social network participation, interpersonal trust, trust in institutions, human capital, managerial skills and hours worked. In this paper these effects are studied using structural equation modelling (SEM) methodology applied to European Social Survey data from 28 European countries in 2018. Schwartz classification of values is used, distinguishing between Self-Enhancement (Power, Achievement), Openness to Change (Self-Direction), Conservation (Tradition, Security, Conformity) and Self-Transcendence (Universalism, Benevolence) values. It is found that Power has the strongest positive direct effect on economic performance, further strengthened by a positive indirect structural effect through hours worked. Self-Direction is indirectly positively linked to economic performance through higher managerial skills and hours worked. Tradition has a strong negative direct effect on economic performance. Security is indirectly negatively linked with economic performance, owing to its negative effects on interpersonal trust, management skills and hours worked. Some of the identified effects are context-dependent and vary across European welfare state regimes. For example, Power is statistically significantly linked to economic performance only in the liberal and conservative regime. Values promoted by respective welfare state regimes are not necessarily associated with higher incomes within those regimes, e.g., Tradition and Security values promoted in the conservative and Mediterranean regime are associated with lower incomes. These findings may lead to a range of policy implications, particularly in relation to the policies on immigration, demographics, the labor market, and work-life balance. Unfortunately, due to the cross-sectional character of the dataset, causal relations among the variables of interest could not be identified.</div
Data on gender.
No full textRich nature of social media data offers a great opportunity to examine social worlds of its users. Further to wide range of topics being discussed on social media, alcohol-related content is prevalent on social media and studies have found an association between this content and increased consumption of alcohol, cravings for alcohol and addiction. This study analyses social media data to examine social worlds of risky drinking in Victoria, Australia. This study conducted a scoping literature review and two online surveys, one with the general community and the other with health professionals, to determine key words to search for on social media sites. These keywords were used in a social media analytics tool called Talkwalker to generate quantitative and qualitative data on the social media users and their conversations. NVIVO was used for developing categories and themes in a sample of 172 posts. A total of 1,021 results were obtained from Twitter. The main demographic group found to be involved in conversations about drinking alcohol on Twitter was young fathers aged 25–34 years. The culture of alcohol consumption in Victoria for Twitter users is reflective of Australia’s drinking culture within which risky drinking, and in particular binge drinking, is normalised.</div
The thermal expansion coefficient of different minerals.
No full textThe thermal expansion coefficient of different minerals.</p
Numerical calculation process.
No full textThe mechanical properties of deep rock masses are significantly influenced by temperature and other factors. The effect of temperature on the strength of deep rock masses will pose a serious challenge to deep resource exploitation and engineering construction. In this paper, the thermal-mechanical coupling calculation model is established by particle flow code (PFC2D) to study the uniaxial compression response of rock masses with microcracks after temperature load. The strength of failure, microcracks, and strain was analyzed. The results show that: (i) When the soft rock thickness ratio Hs/H Hs/H ≥ 0.5, the displacement caused by the applied temperature is concentrated on both sides of the initial microcrack, and the contact force is concentrated in the hard rock area. (ii) The number of microcracks decreases with the increase of soft rock thickness under different working conditions. When the soft rock thickness ratio Hs/H Hs/H ≥ 0.5, the relationship curve between the number of cracks and the vertical strain changes shows three stages of change. (iii) When the soft rock thickness ratio Hs/H T = 100°C and 200°C. When T = 300°C and 400°C, the failure strength decreased first and then increased. When Hs/H ≥ 0.5, the failure strength increases with the increase of soft rock thickness at T = 200°C, 300°C, and 400°C. At T = 100°C, the failure strength decreases with the increase of soft rock thickness.</div