The role of earth observation in an integrated deprived area mapping “system” for low-to-middle income countries

Urbanization in the global South has been accompanied by the proliferation of vast informal and marginalized urban areas that lack access to essential services and infrastructure. UN-Habitat estimates that close to a billion people currently live in these deprived and informal urban settlements, generally grouped under the term of urban slums. Two major knowledge gaps undermine the efforts to monitor progress towards the corresponding sustainable development goal (i.e., SDG 11—Sustainable Cities and Communities). First, the data available for cities worldwide is patchy and insufficient to differentiate between the diversity of urban areas with respect to their access to essential services and their specific infrastructure needs. Second, existing approaches used to map deprived areas (i.e., aggregated household data, Earth observation (EO), and community-driven data collection) are mostly siloed, and, individually, they often lack transferability and scalability and fail to include the opinions of different interest groups. In particular, EO-based-deprived area mapping approaches are mostly top-down, with very little attention given to ground information and interaction with urban communities and stakeholders. Existing top-down methods should be complemented with bottom-up approaches to produce routinely updated, accurate, and timely deprived area maps. In this review, we first assess the strengths and limitations of existing deprived area mapping methods. We then propose an Integrated Deprived Area Mapping System (IDeAMapS) framework that leverages the strengths of EO- and community-based approaches. The proposed framework offers a way forward to map deprived areas globally, routinely, and with maximum accuracy to support SDG 11 monitoring and the needs of different interest groups

Quantum Information Processing with Ferroelectrically Coupled Quantum Dots

I describe a proposal to construct a quantum information processor using ferroelectrically coupled Ge/Si quantum dots. The spin of single electrons form the fundamental qubits. Small (<10 nm diameter) Ge quantum dots are optically excited to create spin polarized electrons in Si. The static polarization of an epitaxial ferroelectric thin film confines electrons laterally in the semiconductor; spin interactions between nearest neighbor electrons are mediated by the nonlinear process of optical rectification. Single qubit operations are achieved through "g-factor engineering" in the Ge/Si structures; spin-spin interactions occur through Heisenberg exchange, controlled by ferroelectric gates. A method for reading out the final state, while required for quantum computing, is not described; electronic approaches involving single electron transistors may prove fruitful in satisfying this requirement.Comment: 10 pages, 3 figure

"Domains of deprivation framework" for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy : a scoping review

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailability of spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, which has been captured in existing literature with a strong focus on household-level deprivation while giving limited attention to area-level deprivation. Within this scoping review, we build on existing literature on household- as well as area-level deprivation frameworks to arrive at a combined understanding of how urban deprivation is defined with a focus on LMIC cities. The scoping review was enriched with local stakeholder workshops in LMIC cities to arrive at our framework of Domains of Deprivations, splitting deprivation into three different scales and nine domains. (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) city Governance (Area Connect scale). The Domains of Deprivation framework provides a clear guidance for collecting data on various aspects of deprivation, while providing the flexibility to decide at city level which indicators are most relevant to explain individual domains. The framework provides a conceptual and operational base for the Integrated Deprived Area Mapping System (IDEAMAPS) Project for the creation of a data ecosystem, which facilitates the production of routine, accurate maps of deprived “slum” areas at scale across cities in LMICs. The Domains of Deprivation Framework is designed to support diverse health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities

“Domains of deprivation framework” for mapping slums, informal settlements, and other deprived areas in LMICs to improve urban planning and policy : a scoping review

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, policy efforts and the monitoring of global goals and agendas such as the United Nation's Sustainable Development Goals (SDGs) and UN-Habitat New Urban Agenda are hindered by the unavailability of statistical and spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, and presently, there is a strong focus within the existing literature on household-level (including individual) deprivation and less on area-level deprivation and this is problematic because deprivation at the area and household-level are known to interrelate and result in multiple challenges for individuals and communities. Within this scoping review, we build on existing literature that focuses on household- or area-level deprivation to arrive at a combined understanding of how urban deprivation is defined in relation to LMIC cities. The scoping review of existing literature was used in conjunction with local stakeholder workshops to produce a framework titled “Domains of Deprivation Framework”. The Domains of Deprivation Framework conceptualizes urban deprivation at three different scales, including at the household scale, within the area scale and at the area connect scale. It includes nine domains, (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) City Governance (Area Connect scale). The Domains of Deprivation Framework is designed to support diverse urban, health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities from a holistic perspective, combining traditional data sources (e.g., surveys or census data) with new data sources (e.g., Earth Observation data)

Need for an integrated deprived area "slum" mapping system (IDEAMAPS) in low-and middle-income countries (LMICS)

Ninety percent of the people added to the planet over the next 30 years will live in African and Asian cities, and a large portion of these populations will reside in deprived neighborhoods defined by slum conditions, informal settlement, or inadequate housing. The four current approaches to neighborhood deprivation mapping are largely siloed, and each fall short of producing accurate, timely, and comparable maps that reflect local contexts. The first approach, classifying "slum households" in census and survey data, reflects household-level rather than neighborhood-level deprivation. The second approach, field-based mapping, can produce the most accurate and context-relevant maps for a given neighborhood, however it requires substantial resources, preventing up-scaling. The third and fourth approaches, human (visual) interpretation and machine classification of air or spaceborne imagery, both overemphasize informal settlements, and fail to represent key social characteristics of deprived areas such as lack of tenure, exposure to pollution, and lack of public services. We summarize common areas of understanding, and present a set of requirements and a framework to produce routine, accurate maps of deprived urban areas that can be used by local-to-international stakeholders for advocacy, planning, and decision-making across Low-and Middle-Income Countries (LMICs). We suggest that machine learning models be extended to incorporate social area-level covariates and regular contributions of up-to-date and context-relevant field-based classification of deprived urban areas

Oral cancer awareness of undergraduate medical and dental students

<p>Abstract</p> <p>Background</p> <p>The incidence of oral cancer is increasing in the United Kingdom. Early detection of oral cancers makes them more amenable to treatment and allows the greatest chance of cure. Delay in presentation and/or referral has a significant effect on the associated morbidity and mortality. Lack of general medical practitioner and general dental practitioner oral cancer knowledge has been shown to contribute to delays in referral and treatment. The aim of this study was to investigate the oral cancer awareness of future general medical and general dental practitioners by assessing undergraduate medical and dental students' knowledge of prevention and early detection of oral cancer.</p> <p>Method</p> <p>Questionnaires were delivered to undergraduate medical and dental students at the University of Dundee, assessing oral examination habits, delivery of advice on oral cancer risk factors, knowledge of oral cancer risk factors and clinical appearance, preferred point of referral and requests for further information.</p> <p>Results</p> <p>Undergraduate medical students were less likely to examine patients' oral mucosa routinely and less likely to advise patients about risk factors for oral cancer. Medical students identified fewer oral cancer risk factors. In particular alcohol use was identified poorly. Medical students also identified fewer oral changes associated with oral cancer. Erythroplakia and erythroleukoplakia were identified poorly. Medical students felt less well informed regarding oral cancer. 86% and 92% of undergraduate medical and dental students respectively requested further information about oral cancer.</p> <p>Conclusion</p> <p>This study highlights the need for improved education of undergraduate medical and dental students regarding oral cancer.</p

Mitotic Spindle Orients Perpendicular to the Forces Imposed by Dynamic Shear

Orientation of the division axis can determine cell fate in the presence of morphogenetic gradients. Understanding how mitotic cells integrate directional cues is therefore an important question in embryogenesis. Here, we investigate the effect of dynamic shear forces on confined mitotic cells. We found that human epithelial cells (hTERT-RPE1) as well as MC3T3 osteoblasts align their mitotic spindle perpendicular to the external force. Spindle orientation appears to be a consequence of cell elongation along the zero-force direction in response to the dynamic shear. This process is a nonlinear response to the strain amplitude, requires actomyosin activity and correlates with redistribution of myosin II. Mechanosteered cells divide normally, suggesting that this mechanism is compatible with biological functions