Ecological Footprint Model Using the Support Vector Machine Technique

The per capita ecological footprint (EF) is one of the most widely recognized measures of environmental sustainability. It aims to quantify the Earth's biological resources required to support human activity. In this paper, we summarize relevant previous literature, and present five factors that influence per capita EF. These factors are: National gross domestic product (GDP), urbanization (independent of economic development), distribution of income (measured by the Gini coefficient), export dependence (measured by the percentage of exports to total GDP), and service intensity (measured by the percentage of service to total GDP). A new ecological footprint model based on a support vector machine (SVM), which is a machine-learning method based on the structural risk minimization principle from statistical learning theory was conducted to calculate the per capita EF of 24 nations using data from 123 nations. The calculation accuracy was measured by average absolute error and average relative error. They were 0.004883 and 0.351078% respectively. Our results demonstrate that the EF model based on SVM has good calculation performance

Four agendas for research and policy on emissions mitigation and well-being

The climate crisis requires nations to achieve human well-being with low national levels of carbon emissions. Countries vary from one another dramatically in how effectively they convert resources into well-being, and some nations with low levels of emissions have relatively high objective and subjective well-being. We identify urgent research and policy agendas for four groups of countries with either low or high emissions and well-being indicators. Least studied are those with low well-being and high emissions. Understanding social and political barriers to switching from high-carbon to lower-carbon modes of production and consumption, and ways to overcome them, will be fundamental

Towards a science of climate and energy choices

The linked problems of energy sustainability and climate change are among the most complex and daunting facing humanity at the start of the twenty-first century. This joint Nature Energy and Nature Climate Change Collection illustrates how understanding and addressing these problems will require an integrated science of coupled human and natural systems; including technological systems, but also extending well beyond the domain of engineering or even economics. It demonstrates the value of replacing the stylized assumptions about human behaviour that are common in policy analysis, with ones based on data-driven science. We draw from and engage articles in the Collection to identify key contributions to understanding non-technological factors connecting economic activity and greenhouse gas emissions, describe a multi-dimensional space of human action on climate and energy issues, and illustrate key themes, dimensions and contributions towards fundamental understanding and informed decision making

Human well‐being and climate change mitigation

Climate change mitigation research is fundamentally motivated by the preservation of human lives and the environmental conditions which enable them. However, the field has to date rather superficial in its appreciation of theoretical claims in well‐being thought, with deep implications for the framing of mitigation priorities, policies, and research. Major strands of well‐being thought are hedonic well‐being—typically referred to as happiness or subjective well‐being—and eudaimonic well‐being, which includes theories of human needs, capabilities, and multidimensional poverty. Aspects of each can be found in political and procedural accounts such as the Sustainable Development Goals. Situating these concepts within the challenges of addressing climate change, the choice of approach is highly consequential for: (1) understanding inter‐ and intra‐generational equity; (2) defining appropriate mitigation strategies; and (3) conceptualizing the socio‐technical provisioning systems that convert biophysical resources into well‐being outcomes. Eudaimonic approaches emphasize the importance of consumption thresholds, beyond which dimensions of well‐being become satiated. Related strands of well‐being and mitigation research suggest constraining consumption to within minimum and maximum consumption levels, inviting normative discussions on the social benefits, climate impacts, and political challenges associated with a given form of provisioning. The question of how current socio‐technical provisioning systems can be shifted towards low‐carbon, well‐being enhancing forms constitutes a new frontier in mitigation research, involving not just technological change and economic incentives, but wide‐ranging social, institutional, and cultural shifts

Unequal household carbon footprints in China

Households’ carbon footprints are unequally distributed among the rich and poor due to differences in the scale and patterns of consumption. We present distributional focused carbon footprints for Chinese households and use a carbon-footprint-Gini coefficient to quantify inequalities. We find that in 2012 the urban very rich, comprising 5% of population, induced 19% of the total carbon footprint from household consumption in China, with 6.4 tCO2/cap. The average Chinese household footprint remains comparatively low (1.7 tCO2/cap), while those of the rural population and urban poor, comprising 58% of population, are 0.5–1.6 tCO2/cap. Between 2007 and 2012 the total footprint from households increased by 19%, with 75% of the increase due to growing consumption of the urban middle class and the rich. This suggests that a transformation of Chinese lifestyles away from the current trajectory of carbon-intensive consumption patterns requires policy interventions to improve living standards and encourage sustainable consumption

Gene-Centric Characteristics of Genome-Wide Association Studies

BACKGROUND: The high-throughput genotyping chips have contributed greatly to genome-wide association (GWA) studies to identify novel disease susceptibility single nucleotide polymorphisms (SNPs). The high-density chips are designed using two different SNP selection approaches, the direct gene-centric approach, and the indirect quasi-random SNPs or linkage disequilibrium (LD)-based tagSNPs approaches. Although all these approaches can provide high genome coverage and ascertain variants in genes, it is not clear to which extent these approaches could capture the common genic variants. It is also important to characterize and compare the differences between these approaches. METHODOLOGY/PRINCIPAL FINDINGS: In our study, by using both the Phase II HapMap data and the disease variants extracted from OMIM, a gene-centric evaluation was first performed to evaluate the ability of the approaches in capturing the disease variants in Caucasian population. Then the distribution patterns of SNPs were also characterized in genic regions, evolutionarily conserved introns and nongenic regions, ontologies and pathways. The results show that, no mater which SNP selection approach is used, the current high-density SNP chips provide very high coverage in genic regions and can capture most of known common disease variants under HapMap frame. The results also show that the differences between the direct and the indirect approaches are relatively small. Both have similar SNP distribution patterns in these gene-centric characteristics. CONCLUSIONS/SIGNIFICANCE: This study suggests that the indirect approaches not only have the advantage of high coverage but also are useful for studies focusing on various functional SNPs either in genes or in the conserved regions that the direct approach supports. The study and the annotation of characteristics will be helpful for designing and analyzing GWA studies that aim to identify genetic risk factors involved in common diseases, especially variants in genes and conserved regions

How do pharmacists in English general practices identify their impact? An exploratory qualitative study of measurement problems

Background: In England, there is an ongoing national pilot to expand pharmacists’ presence in general practice. Evaluation of the pilot includes numerical and survey-based Key Performance Indicators (KPIs) and requires pharmacists to electronically record their activities, possibly by using activity codes. At the time of the study (2016), no national evaluation of pharmacists’ impact in this environment had been formally announced. The aim of this qualitative study was to identify problems that English pharmacists face when measuring and recording their impact in general practice. Methods: All pharmacists, general practitioners (GPs) and practice managers working across two West London pilot sites were invited, via e-mail, to participate in a focus group study. Appropriately trained facilitators conducted two audio-recorded, semi-structured focus groups, each lasting approximately one hour, to explore experiences and perceptions associated with the KPIs. Audio-recordings were transcribed verbatim and the data analysed thematically. Results: In total, 13 pharmacists, one GP and one practice manager took part in the study. Four major themes were discerned: inappropriateness of the numerical national KPIs (“whether or not we actually have positive impact on KPIs is beyond our control”); depth and breadth of pharmacists’ activity (“we see a huge plethora of different patients and go through this holistic approach - everything is looked at”); awareness of practice based pharmacists’ roles (“I think the really important [thing] is that everyone knows what pharmacists in general practice are doing”); and central evaluation versus local initiatives (“the KPIs will be measured by National Health Service England regardless of what we think” versus “what I think is more pertinent, are there some local things we’re going to measure?”). Conclusions: Measures that will effectively capture pharmacists’ impact in general practice should be developed, along with a set of codes reflecting the whole spectrum of pharmacists’ activities. Our study also points out the significance of a transparent, robust national evaluation, including exploring the needs/expectations of practice staff and patients regarding pharmacists’ presence in general practice