556 resultados para affordable


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China’s urbanization and industrialization are occupying farmland in large amounts, which is strongly driven by land finance regime. This is due to the intensified regional/local competition for manufacturing investment opportunities that push local governments to expropriate farmland at low prices while lease land at high market value to property developers. The additional revenue obtained in this way, termed financial increment in land values, can drive local economic growth, and provide associated infrastructure and other public services. At the same time, however, a floating population of large numbers of inadequately compensated land-lost farmers, although unable to become citizens, have to migrate into the urban areas for work, causing overheated employment and housing markets, with rocketing unaffordable housing prices. This, together with various micro factors relating to the party/state’s promotion/evaluation system play an essential role leading to some serious economic, environment and social consequences, e.g., on migrant welfare, the displacement of peasants and the loss of land resources that requires immediate attention. Our question is: whether such type of urbanization is sustainable? What are the mechanisms behind such a phenomenal urbanization process? From the perspective of institutionalism, this paper aims to investigate the institutional background of the urban growth dilemma and solutions in urban China and to introduce further an inter-regional game theoretical framework to indicate why the present urbanization pattern is unsustainable. Looking forward to 2030, paradigm policy changes are made from the triple consideration of floating population, social security and urban environmental pressures. This involves: (1) changing land increment based finance regime into land stock finance system; (2) the citizenization of migrant workers with affordable housing, and; (3) creating a more enlightened local government officer appraisal system to better take into account societal issues such as welfare and beyond.

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The Master’s thesis is qualitative research based on interviews of 15 Chinese immigrants to Finland in order to provide a sociological perspective of the migration experience through the eyes of Chinese immigrants in the Finnish social welfare context. This research is mainly focused upon four crucial aspects of life in the settlement process: housing, employment, access to health care and child care. Inspired by Allardt’s theoretical framework ‘Having, Loving and Being’, social relationships and individual satisfaction are examined in the case of Chinese interviewees dealing with the four life aspects. Finland was not perceived as an attractive migration destination for most Chinese interviewees in the beginning. However, with longer residence in Finland, the Finnish social welfare system gradually became a crucial appealing factor in their permanent settlement in Finland. And meanwhile, social responsibility of attending their old parents in China, strong feelings of being isolated in Finland, and insufficient integration into the Finnish society were influential factors for their decision of returning to China. Social relationships with personal friends, migration brokers, schools, employers and family relatives had great influences in the four life aspects of Chinese immigrants in Finland. The social relationship with the Finnish social welfare sector is supportive to Chinese immigrants, but Chinese immigrants do not heavily rely on Finnish social protection. The housing conditions were greatly improved over time while the upward mobility in the Finnish labour market was not significant among Chinese immigrants. All Chinese immigrants were satisfied with their current housing by the time I interviewed them while most of them had subjective feelings of being alienated in the Finnish labour market, which seriously prevented them from integrating into the Finnish society. In general, Chinese immigrants were satisfied with the low cost of accessing the Finnish public health care services and affordable Finnish child day care services and financial subsidies for children from the Finnish social welfare sector. This research also suggests that employment is the central basis in well-being. Support from the Finnish social welfare sector can improve the satisfaction levels among immigrants, especially when it mitigates the effects of low-paid employment. As well, my empirical study of Chinese immigrants in Finland shows that Having (needs for materials), Loving (needs for social relations) and Being (needs for social integration) are all involved in the four concrete aspects (housing, employment, access to health care and child care).

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The technical developments and advances that have taken place thus far are reviewed in those areas impacting future phased array active aperture radar systems. The areas covered are printed circuit antennas and antenna arrays, GaAs MMIC design and fabrication leading to affordable transmitter-receiver (T-R) modules, and novel hardware and software developments. The use of fiber-optic distribution networks to interconnect the monolithically integrated optical components with the T-R modules is discussed. Beamforming and sidelobe control techniques for active phased array systems are also examined.

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Large MIMO systems with tens of antennas in each communication terminal using full-rate non-orthogonal space-time block codes (STBC) from Cyclic Division Algebras (CDA) can achieve the benefits of both transmit diversity as well as high spectral efficiencies. Maximum-likelihood (ML) or near-ML decoding of these large-sized STBCs at low complexities, however, has been a challenge. In this paper, we establish that near-ML decoding of these large STBCs is possible at practically affordable low complexities. We show that the likelihood ascent search (LAS) detector, reported earlier by us for V-BLAST, is able to achieve near-ML uncoded BER performance in decoding a 32x32 STBC from CDA, which employs 32 transmit antennas and sends 32(2) = 1024 complex data symbols in 32 time slots in one STBC matrix (i.e., 32 data symbols sent per channel use). In terms of coded BER, with a 16x16 STBC, rate-3/4 turbo code and 4-QAM (i.e., 24 bps/Hz), the LAS detector performs close to within just about 4 dB from the theoretical MIMO capacity. Our results further show that, with LAS detection, information lossless (ILL) STBCs perform almost as good as full-diversity ILL (FD-ILL) STBCs. Such low-complexity detectors can potentially enable implementation of high spectral efficiency large MIMO systems that could be considered in wireless standards.

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An (alpha, beta)-spanner of an unweighted graph G is a subgraph H that distorts distances in G up to a multiplicative factor of a and an additive term beta. It is well known that any graph contains a (multiplicative) (2k - 1, 0)-spanner of size O(n(1+1/k)) and an (additive) (1, 2)-spanner of size O(n(3/2)). However no other additive spanners are known to exist. In this article we develop a couple of new techniques for constructing (alpha, beta)-spanners. Our first result is an additive (1, 6)-spanner of size O(n(4/3)). The construction algorithm can be understood as an economical agent that assigns costs and values to paths in the graph, purchasing affordable paths and ignoring expensive ones, which are intuitively well approximated by paths already purchased. We show that this path buying algorithm can be parameterized in different ways to yield other sparseness-distortion tradeoffs. Our second result addresses the problem of which (alpha, beta)-spanners can be computed efficiently, ideally in linear time. We show that, for any k, a (k, k - 1)-spanner with size O(kn(1+1/k)) can be found in linear time, and, further, that in a distributed network the algorithm terminates in a constant number of rounds. Previous spanner constructions with similar performance had roughly twice the multiplicative distortion.

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Ethnopharmacological relevance: Malaria is a serious public health problem in the north-eastern region of India including Assam, in view of development of chloroquine resistant Plasmodium falciparum. There is need for alternative and affordable therapy. Aim of the study: This study was conducted to document indigenous knowledge, usage customs and practices of medicinal plant species traditionally used by the residents of Sonitpur district of Tezpur, Assam to treat malaria and its associated symptoms. Materials and methods:A total of 50 randomly selected sampling represented by male (38.76%) and female respondents (12.24%) were interviewed using a semi-structured questionnaire. Results: The present ethno-botanical survey revealed 22 species of plants belonging to 17 botanical families were reported to be used exclusively in this region for the treatment of malaria. Verbenaceae (three species), Menispermaceae (two species), and Acanthaceae (two species) botanical families represented the species that are most commonly cited in this survey work and the detailed use of plants has been collected and described. Conclusions: The most serious threat to the existing knowledge and practice on traditional medicinal plants included cultural change, particularly the influence of modernization and lack of interests shown by the next younger generations were the main problems reported by the informants during the field survey. Hence, the proper documentation of traditional medicinal plants being used as anti-malarial agents and related indigenous knowledge held by the tribal community is an important approach to control the spread of vector-borne diseases like malaria reported in this survey work. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

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Expanding energy access to the rural population of India presents a critical challenge for its government. The presence of 364 million people without access to electricity and 726 million who rely on biomass for cooking indicate both the failure of past policies and programs, and the need for a radical redesign of the current system. We propose an integrated implementation framework with recommendations for adopting business principles with innovative institutional, regulatory, financing and delivery mechanisms. The framework entails establishment of rural energy access authorities and energy access funds, both at the national and regional levels, to be empowered with enabling regulatory policies, capital resources and the support of multi-stakeholder partnership. These institutions are expected to design, lead, manage and monitor the rural energy interventions. At the other end, trained entrepreneurs would be expected to establish bioenergy-based micro-enterprises that will produce and distribute energy carriers to rural households at an affordable cost. The ESCOs will function as intermediaries between these enterprises and the international carbon market both in aggregating carbon credits and in trading them under CDM. If implemented, such a program could address the challenges of rural energy empowerment by creating access to modern energy carriers and climate change mitigation. (C) 2011 Elsevier Ltd. All rights reserved.

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A transient flame simulation tool based on unsteady Reynolds average Navier Stokes (RANS) is characterized for stationary and nonstationary flame applications with a motivation of performing computationally affordable flame stability studies. Specifically, the KIVA-3V code is utilized with incorporation of a recently proposed modified eddy dissipation concept for simulating turbulence-chemistry interaction along with a model for radiation loss. Detailed comparison of velocities, turbulent kinetic energies, temperature, and species are made with the experimental data of the turbulent, non-premixed DLR_A CH4/H-2/N-2 jet flame. The comparison shows that the model is able to predict flame structure very well. The effect of some of the modeling assumptions is assessed, and strategies to model a stationary diffusion flame are recommended. Unsteady flame simulation capabilities of the numerical model are assessed by simulating an acoustically excited, experimental, oscillatory H-2-air diffusion flame. Comparisons are made with oscillatory velocity field and OH plots, and the numerical code is observed to predict transient flame structure well.

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Background & objectives: There is a need to develop an affordable and reliable tool for hearing screening of neonates in resource constrained, medically underserved areas of developing nations. This study valuates a strategy of health worker based screening of neonates using a low cost mechanical calibrated noisemaker followed up with parental monitoring of age appropriate auditory milestones for detecting severe-profound hearing impairment in infants by 6 months of age. Methods: A trained health worker under the supervision of a qualified audiologist screened 425 neonates of whom 20 had confirmed severe-profound hearing impairment. Mechanical calibrated noisemakers of 50, 60, 70 and 80 dB (A) were used to elicit the behavioural responses. The parents of screened neonates were instructed to monitor the normal language and auditory milestones till 6 months of age. This strategy was validated against the reference standard consisting of a battery of tests - namely, auditory brain stem response (ABR), otoacoustic emissions (OAE) and behavioural assessment at 2 years of age. Bayesian prevalence weighted measures of screening were calculated. Results: The sensitivity and specificity was high with least false positive referrals for. 70 and 80 dB (A) noisemakers. All the noisemakers had 100 per cent negative predictive value. 70 and 80 dB (A) noisemakers had high positive likelihood ratios of 19 and 34, respectively. The probability differences for pre- and post- test positive was 43 and 58 for 70 and 80 dB (A) noisemakers, respectively. Interpretation & conclusions: In a controlled setting, health workers with primary education can be trained to use a mechanical calibrated noisemaker made of locally available material to reliably screen for severe-profound hearing loss in neonates. The monitoring of auditory responses could be done by informed parents. Multi-centre field trials of this strategy need to be carried out to examine the feasibility of community health care workers using it in resource constrained settings of developing nations to implement an effective national neonatal hearing screening programme.

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It is well accepted that technology plays a critical role in socio-technical transitions, and sustainable development pathways. A society‘s amenability to the intervening (sustainable) technology is fundamental to permit these transitions. The current age is at a juncture wherein technological advancements and capacities provide the common individual with affordable and unlimited choice. Technological advancement and complexity can either remain simple and unseen to the user or may daunt him to keep away, in which case the intended pathways remain unexploited. The current paper explores the reasons behind rejection of technology and proposes a solution model to address these factors in accommodating socio-technical transitions. The paper begins with structuring the societal levels at which technological rejection occurs and proceeds to discuss technology rejection at the individual user (niche)level. The factors influencing decisions regarding technology rejection are identified and discussed with particular relevance to the progressive world (Asia).

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India's energy challenges are three pronged: presence of majority energy poor lacking access to modern energy; need for expanding energy system to bridge this access gap as well as to meet the requirements of fast-growing economy; and the desire to partner with global economies in mitigating the threat of climate change. The presence of 364 million people without access to electricity and 726 million relying on biomass for cooking out of a total rural population of 809 million indicate the seriousness of challenge. In this paper, we discuss an innovative approach to address this challenge, which intends to take advantage of recent global developments and untapped capabilities possessed by India. Intention is to use climate change mitigation imperative as a stimulus and adopt a public-private-partnership-driven ‘business model' with innovative institutional, regulatory, financing, and delivery mechanisms. Some of the innovations are: creation of rural energy access authorities within the government system as leadership institutions; establishment of energy access funds to enable transitions from the regime of "investment/fuel subsidies" to "incentive-linked" delivery of energy services; integration of business principles to facilitate affordable and equitable energy sales and carbon trade; and treatment of entrepreneurs as implementation targets. This proposal targets 100% access to modern energy carriers by 2030 through a judicious mix of conventional and biomass energy systems with an investment of US$35 billion over 20 years. The estimated annual cost of universal energy access is about US$9 billion for a GHG mitigation potential of 213Tg CO2e at an abatement cost of US$41/tCO2e. It is a win-win situation for all stakeholders. Households benefit from modern energy carriers at affordable cost; entrepreneurs run profitable energy enterprises; carbon markets have access to CERs; the government has the satisfaction of securing energy access to rural people; and globally, there is a benefit of climate change mitigation.

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Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.

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While the world is focused on controlling the spread of diseases such as HIV and malaria in the developing world, another approaching epidemic has been largely overlooked. The World Heath Organization predicts that there will be 16 million new cancer cases per year in 2020 and 70% of these will be in the developing world. Many of these cancers are preventable, or treatable when detected early enough. Establishing effective, affordable and workable cancer control plans in African countries is one step in the right direction toward limiting this epidemic.

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In this paper we introduce four scenario Cluster based Lagrangian Decomposition (CLD) procedures for obtaining strong lower bounds to the (optimal) solution value of two-stage stochastic mixed 0-1 problems. At each iteration of the Lagrangian based procedures, the traditional aim consists of obtaining the solution value of the corresponding Lagrangian dual via solving scenario submodels once the nonanticipativity constraints have been dualized. Instead of considering a splitting variable representation over the set of scenarios, we propose to decompose the model into a set of scenario clusters. We compare the computational performance of the four Lagrange multiplier updating procedures, namely the Subgradient Method, the Volume Algorithm, the Progressive Hedging Algorithm and the Dynamic Constrained Cutting Plane scheme for different numbers of scenario clusters and different dimensions of the original problem. Our computational experience shows that the CLD bound and its computational effort depend on the number of scenario clusters to consider. In any case, our results show that the CLD procedures outperform the traditional LD scheme for single scenarios both in the quality of the bounds and computational effort. All the procedures have been implemented in a C++ experimental code. A broad computational experience is reported on a test of randomly generated instances by using the MIP solvers COIN-OR and CPLEX for the auxiliary mixed 0-1 cluster submodels, this last solver within the open source engine COIN-OR. We also give computational evidence of the model tightening effect that the preprocessing techniques, cut generation and appending and parallel computing tools have in stochastic integer optimization. Finally, we have observed that the plain use of both solvers does not provide the optimal solution of the instances included in the testbed with which we have experimented but for two toy instances in affordable elapsed time. On the other hand the proposed procedures provide strong lower bounds (or the same solution value) in a considerably shorter elapsed time for the quasi-optimal solution obtained by other means for the original stochastic problem.

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Executive Summary: Tropical marine ecosystems in the Caribbean region are inextricably linked through the movement of pollutants, nutrients, diseases, and other stressors, which threaten to further degrade coral reef communities. The magnitude of change that is occurring within the region is considerable, and solutions will require investigating pros and cons of networks of marine protected areas (MPAs), cooperation of neighboring countries, improved understanding of how external stressors degrade local marine resources, and ameliorating those stressors. Connectivity can be broadly defined as the exchange of materials (e.g., nutrients and pollutants), organisms, and genes and can be divided into: 1) genetic or evolutionary connectivity that concerns the exchange of organisms and genes, 2) demographic connectivity, which is the exchange of individuals among local groups, and 3) oceanographic connectivity, which includes flow of materials and circulation patterns and variability that underpin much of all these exchanges. Presently, we understand little about connectivity at specific locations beyond model outputs, and yet we must manage MPAs with connectivity in mind. A key to successful MPA management is how to most effectively work with scientists to acquire the information managers need. Oceanography connectivity is poorly understood, and even less is known about the shape of the dispersal curve for most species. Dispersal kernels differ for various systems, species, and life histories and are likely highly variable in space and time. Furthermore, the implications of different dispersal kernels on population dynamics and management of species is unknown. However, small dispersal kernels are the norm - not the exception. Linking patterns of dispersal to management options is difficult given the present state of knowledge. The behavioral component of larval dispersal has a major impact on where larvae settle. Individual larval behavior and life history details are required to produce meaningful simulations of population connectivity. Biological inputs are critical determinants of dispersal outcomes beyond what can be gleaned from models of passive dispersal. There is considerable temporal and spatial variation to connectivity patterns. New models are increasingly being developed, but these must be validated to understand upstream-downstream neighborhoods, dispersal corridors, stepping stones, and source/sink dynamics. At present, models are mainly useful for providing generalities and generating hypotheses. Low-technology approaches such as drifter vials and oceanographic drogues are useful, affordable options for understanding local connectivity. The “silver bullet” approach to MPA design may not be possible for several reasons. Genetic connectivity studies reveal divergent population genetic structures despite similar larval life histories. Historical stochasticity in reproduction and/or recruitment likely has important, longlasting consequences on present day genetic structure. (PDF has 200 pages.)