204 research outputs found

    Economic valuation of development projects : a case study of a non-motorized transport project in India

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    One of the major difficulties in doing cost-benefit analysis of a development project is to estimate the total economic value of project benefits, which are usually multi-dimensional andinclude goods and services that are not traded in the market. Challenges also arise in aggregating the values of different benefits, which may not be mutually exclusive. This paper uses a contingent valuation approach to estimate the economic value of a non-motorized transport project in Pune, India, across beneficiaries. The heads of households which are potentially affected by the project are presented with a detailed description of the project, and then are asked to vote on whether such a project should be undertaken given different specifications of costs to the households. The total value of the project is then derived from the survey answers. Econometric analysis indicates that the survey responses provide generally reasonable valuation estimates.Transport Economics Policy&Planning,Environmental Economics&Policies,Roads&Highways,Housing&Human Habitats,Economic Theory&Research

    Valuing water quality improvement in China : a case study of lake Puzhehei in Yunnan province

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    While polluted surface water is encountered across most of China, few economic valuation studies have been conducted on water quality changes. Limited information about the economic values associated with those potential water quality improvements or deteriorations is a disadvantage for making proper choices in water pollution control and clean-up activities. This paper reports an economic valuation study conducted in Yunnan, China, which aims to estimate the total value of a real investment project to improve the water quality of Lake Puzhehei by one grade level. Located in Qiubei County, which is far from large cities, the lake has been experiencing fast water quality deterioration in the past years. A conservative estimation strategy shows that on average a household located in Qiubei County is willing to pay about 30 yuan per month continuously for 5 years for water quality improvement, equivalent roughly to 3 percent of household income. The elasticity of willingness-to-pay with respect to income is estimated to be 0.21. The economic rate of return of the proposed project is estimated to be 18 percent, indicating a strong demand and high efficiency of investment in water quality improvement in China. This study also demonstrates that previous knowledge about water quality changes and the project may have a significant positive impact on people's valuation, and that the interviewer effect on valuation can be negative.Water and Industry,Environmental Economics&Policies,Water Supply and Sanitation Governance and Institutions,Town Water Supply and Sanitation,Water Supply and Systems

    Competitive Ensembling Teacher-Student Framework for Semi-Supervised Left Atrium MRI Segmentation

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    Semi-supervised learning has greatly advanced medical image segmentation since it effectively alleviates the need of acquiring abundant annotations from experts and utilizes unlabeled data which is much easier to acquire. Among existing perturbed consistency learning methods, mean-teacher model serves as a standard baseline for semi-supervised medical image segmentation. In this paper, we present a simple yet efficient competitive ensembling teacher student framework for semi-supervised for left atrium segmentation from 3D MR images, in which two student models with different task-level disturbances are introduced to learn mutually, while a competitive ensembling strategy is performed to ensemble more reliable information to teacher model. Different from the one-way transfer between teacher and student models, our framework facilitates the collaborative learning procedure of different student models with the guidance of teacher model and motivates different training networks for a competitive learning and ensembling procedure to achieve better performance. We evaluate our proposed method on the public Left Atrium (LA) dataset and it obtains impressive performance gains by exploiting the unlabeled data effectively and outperforms several existing semi-supervised methods.Comment: Accepeted for BIBM 202

    Degradation Estimation Recurrent Neural Network with Local and Non-Local Priors for Compressive Spectral Imaging

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    In the Coded Aperture Snapshot Spectral Imaging (CASSI) system, deep unfolding networks (DUNs) have demonstrated excellent performance in recovering 3D hyperspectral images (HSIs) from 2D measurements. However, some noticeable gaps exist between the imaging model used in DUNs and the real CASSI imaging process, such as the sensing error as well as photon and dark current noise, compromising the accuracy of solving the data subproblem and the prior subproblem in DUNs. To address this issue, we propose a Degradation Estimation Network (DEN) to correct the imaging model used in DUNs by simultaneously estimating the sensing error and the noise level, thereby improving the performance of DUNs. Additionally, we propose an efficient Local and Non-local Transformer (LNLT) to solve the prior subproblem, which not only effectively models local and non-local similarities but also reduces the computational cost of the window-based global Multi-head Self-attention (MSA). Furthermore, we transform the DUN into a Recurrent Neural Network (RNN) by sharing parameters of DNNs across stages, which not only allows DNN to be trained more adequately but also significantly reduces the number of parameters. The proposed DERNN-LNLT achieves state-of-the-art (SOTA) performance with fewer parameters on both simulation and real datasets

    Residual Degradation Learning Unfolding Framework with Mixing Priors across Spectral and Spatial for Compressive Spectral Imaging

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    To acquire a snapshot spectral image, coded aperture snapshot spectral imaging (CASSI) is proposed. A core problem of the CASSI system is to recover the reliable and fine underlying 3D spectral cube from the 2D measurement. By alternately solving a data subproblem and a prior subproblem, deep unfolding methods achieve good performance. However, in the data subproblem, the used sensing matrix is ill-suited for the real degradation process due to the device errors caused by phase aberration, distortion; in the prior subproblem, it is important to design a suitable model to jointly exploit both spatial and spectral priors. In this paper, we propose a Residual Degradation Learning Unfolding Framework (RDLUF), which bridges the gap between the sensing matrix and the degradation process. Moreover, a MixS2S^2 Transformer is designed via mixing priors across spectral and spatial to strengthen the spectral-spatial representation capability. Finally, plugging the MixS2S^2 Transformer into the RDLUF leads to an end-to-end trainable neural network RDLUF-MixS2S^2. Experimental results establish the superior performance of the proposed method over existing ones.Comment: 10 pages, 5 figure

    DJ-1 can inhibit microtubule associated protein 1 B formed aggregates

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    <p>Abstract</p> <p>Background</p> <p>Abnormal accumulation and aggregation of microtubule associated proteins (MAPs) plays an important role in the pathogenesis of neurodegenerative diseases. Loss-of-function mutation of DJ-1/Park7 can cause early onset of PD. DJ-1, a molecular chaperone, can inhibit Îą-synuclein aggregation. Currently, little is known whether or not loss of function of DJ-1 contributes to abnormal MAPs aggregation in neurodegenerative disorders such as PD.</p> <p>Results</p> <p>We presented evidence that DJ-1 could bind to microtubule associated protein1b Light Chain (MAP1b-LC). Overexpression of DJ-1 prevented MAP1b-LC aggregation in HEK293t and SH-SY5Y cells while DJ-1 knocking down (KD) enhanced MAP1b-LC aggregation in SH-SY5Y cells. The increase in insoluble MAP1b-LC was also observed in the DJ-1 null mice brain. Moreover, in the DJ-1 KD SH-SY5Y cells, overexpression of MAP1B-LC led to endoplasmic reticulum (ER) stress-induced apoptosis.</p> <p>Conclusion</p> <p>Our results suggest that DJ-1 acts as a molecular chaperone to inhibit MAP1B aggregation thus leading to neuronal apoptosis. Our study provides a novel insight into the mechanisms that underly the pathogenesis of Parkinson's disease (PD).</p

    Implementation-effectiveness trial of an ecological intervention for physical activity in ethnically diverse low income senior centers.

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    BackgroundAs the US population ages, there is an increasing need for evidence based, peer-led physical activity programs, particularly in ethnically diverse, low income senior centers where access is limited.Methods/designThe Peer Empowerment Program 4 Physical Activity' (PEP4PA) is a hybrid Type II implementation-effectiveness trial that is a peer-led physical activity (PA) intervention based on the ecological model of behavior change. The initial phase is a cluster randomized control trial randomized to either a peer-led PA intervention or usual center programming. After 18 months, the intervention sites are further randomized to continued support or no support for another 6 months. This study will be conducted at twelve senior centers in San Diego County in low income, diverse communities. In the intervention sites, 24 peer health coaches and 408 adults, aged 50 years and older, are invited to participate. Peer health coaches receive training and support and utilize a tablet computer for delivery and tracking. There are several levels of intervention. Individual components include pedometers, step goals, counseling, and feedback charts. Interpersonal components include group walks, group sharing and health tips, and monthly celebrations. Community components include review of PA resources, walkability audit, sustainability plan, and streetscape improvements. The primary outcome of interest is intensity and location of PA minutes per day, measured every 6 months by wrist and hip accelerometers and GPS devices. Secondary outcomes include blood pressure, physical, cognitive, and emotional functioning. Implementation measures include appropriateness &amp; acceptability (perceived and actual fit), adoption &amp; penetration (reach), fidelity (quantity &amp; quality of intervention delivered), acceptability (satisfaction), costs, and sustainability.DiscussionUsing a peer led implementation strategy to deliver a multi-level community based PA program can enhance program adoption, implementation, and sustainment.Trial registrationClinicalTrials.gov, USA ( NCT02405325 ). Date of registration, March 20, 2015. This website also contains all items from the World Health Organization Trial Registration Data Set
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