Bias adjustment of infrared-based rainfall estimation using Passive Microwave satellite rainfall data

This study explores using Passive Microwave (PMW) rainfall estimation for spatial and temporal adjustment of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System(PERSIANN-CCS). The PERSIANN-CCS algorithm collects information from infrared images to estimate rainfall. PERSIANN-CCS is one of the algorithms used in the IntegratedMultisatellite Retrievals for GPM (Global Precipitation Mission) estimation for the time period PMW rainfall estimations are limited or not available. Continued improvement of PERSIANN-CCS will support Integrated Multisatellite Retrievals for GPM for current as well as retrospective estimations of global precipitation. This study takes advantage of the high spatial and temporal resolution of GEO-based PERSIANN-CCS estimation and the more effective, but lower sample frequency, PMW estimation. The Probability Matching Method (PMM) was used to adjust the rainfall distribution of GEO-based PERSIANN-CCS toward that of PMW rainfall estimation. The results show that a significant improvement of global PERSIANN-CCS rainfall estimation is obtained

A scheme for cancelling intercarrier interference using conjugate transmission in multicarrier communication systems

To mitigate intercarrier interference (ICI), a two-path algorithm is developed for multicarrier communication systems, including orthogonal frequency division multiplexing (OFDM) systems. The first path employs the regular OFDM algorithm. The second path uses the conjugate transmission of the first path. The combination of both paths forms a conjugate ICI cancellation scheme at the receiver. This conjugate cancellation (CC) scheme provides (1) a high signal to interference power ratio (SIR) in the presence of small frequency offsets (50 dB and 33 dB higher than that of the regular OFDM and linear self-cancellation algorithms [1], [2], respectively, at ΔfT = 0.1% of subcarrier frequency spacing); (2) better bit error rate (BER) performance in both additive white Gaussian noise (AWGN) and fading channels; (3) backward compatibility with the existing OFDM system; (4) no channel equalization is needed for reducing ICI, a simple low cost receiver without increasing system complexity. Although the two-path transmission reduces bandwidth efficiency, the disadvantage can be balanced by increasing signal alphabet sizes

Deep Learning for Forecasting Stock Returns in the Cross-Section

Many studies have been undertaken by using machine learning techniques, including neural networks, to predict stock returns. Recently, a method known as deep learning, which achieves high performance mainly in image recognition and speech recognition, has attracted attention in the machine learning field. This paper implements deep learning to predict one-month-ahead stock returns in the cross-section in the Japanese stock market and investigates the performance of the method. Our results show that deep neural networks generally outperform shallow neural networks, and the best networks also outperform representative machine learning models. These results indicate that deep learning shows promise as a skillful machine learning method to predict stock returns in the cross-section.Comment: 12 pages, 2 figures, 8 tables, accepted at PAKDD 201

Individual patient data meta-analysis of randomized controlled trials of community occupational therapy for stroke patients

<p><b>Background and Purpose:</b> Trials of occupational therapy for stroke patients living in the community have varied in their findings. It is unclear why these discrepancies have occurred.</p> <p><b>Methods:</b> Trials were identified from searches of the Cochrane Library and other sources. The primary outcome measure was the Nottingham Extended Activities of Daily Living (NEADL) score at the end of intervention. Secondary outcome measures included the Barthel Index or the Rivermead ADL (Personal ADL), General Health Questionnaire (GHQ), Nottingham Leisure Questionnaire (NLQ), and death. Data were analyzed using linear or logistic regression with a random effect for trial and adjustment for age, gender, baseline dependency, and method of follow-up. Subgroup analyses compared any occupational therapy intervention with control.</p> <p><b>Results:</b> We included 8 single-blind randomized controlled trials incorporating 1143 patients. Occupational therapy was associated with higher NEADL scores at the end of intervention (weighted mean difference [WMD], 1.30 points, 95% confidence intervals [CI], 0.47 to 2.13) and higher leisure scores at the end of intervention (WMD, 1.51 points; 95% CI, 0.24 to 2.79). Occupational therapy emphasizing activities of daily living (ADL) was associated with improved end of intervention NEADL (WMD, 1.61 points; 95% CI, 0.72 to 2.49) and personal activities of daily living (odds ratio [OR], 0.65; 95% CI, 0.46 to 0.91), but not NLQ. Leisure-based occupational therapy improved end of intervention NLQ (WMD, 1.96 points; 95% CI, 0.27 to 3.66) but not NEADL or PADL.</p> <p><b>Conclusions:</b> Community occupational therapy significantly improved personal and extended activities of daily living and leisure activity in patients with stroke. Better outcomes were found with targeted interventions.</p&gt

Economic Integration in East Asia: Trends, Prospects, and a Possible Roadmap

This paper, which is a revised version of the ADB Working Paper on Regional Economic Integration No. 2, reviews trends in East Asian regionalism in the areas of trade and investment, money and finance, and infrastructure. It finds that trade and, to a lesser extent, financial integration is starting to increase in the region. It also finds that business cycles are starting to be more synchronized, enhancing the case for further monetary integration among these countries. The paper also outlines a roadmap for East Asian integration.

Economic Integration in East Asia: Trends, Prospects, and a Possible Roadmap

This paper reviews trends in East Asian regionalism in the areas of trade and investment, money and finance, and infrastructure. It presents various measures of trade and financial integration. An important finding of the paper is that increasing trade and financial integration in the region is now starting to lead to a synchronization of business cycles in a selected group of countries, further enhancing the case for monetary integration among these countries. The paper also outlines a roadmap for East Asian integration.ASEAN/East Asian economic cooperation and integration; business cycle synchronization; free trade agreements; policy coordination

Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009–2014. The historical data (satellite and gauge) for 2009–2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide

Remotely sensed dune celerity and sand flux measurements of the world's fastest barchans (Bodele, Chad)

Quantifying sand flux with field measurements is an expensive and time-consuming process. We here present an alternative approach using the COSI-Corr software package for Earth surface deformation detection. Using pairs of ASTER satellite images, we detected dune migration in the Bodélé depression of northern Chad over time intervals of one month to 6.5 years. The displacement map can be used to automatically distinguish dunes from interdunes, which is a crucial step towards calculating sand flux. We interpolated a surface between the interdune areas and subtracted it from a digital elevation model, thus obtaining dune heights and volumes. Multiplying height with celerity yields a pixel-by-pixel estimate of the sand flux. We applied this method to large diatomite dunes in the Bodélé, confirming that these are some of the world's fastest moving barchans. Plotting dune height against inverse celerity reveals sand flux at the dune crest of >200 m3/m/yr. Average dune sand flux values for the eastern and western Bodélé are 76 and 99 m3/m/yr, respectively. The contribution of the dunes to the total area-averaged sand flux is 24–29 m3/m/yr, which is ∼10% of the saltation flux determined by previously published field measurements

The Effects of the Minimum Wage in the Private and Public Sectors in Brazil

The wage and employment effects of the minimum wage predicted by the standard neoclassical theory rely on a profit maximizing firm, not on a Government employer that can cover the higher wage bill by raising taxes, reducing expenditure, or simply printing money. If the public sector has an inelastic labour demand, the associated non-negative employment effect might offset some of the negative employment effect observed in the private sector and the overall employment effect might be less adverse. This is particularly so if the public sector is overpopulated by minimum wage workers, as in Brazil. There is very limited evidence on the minimum wage effects in developing countries, and none whatsoever on the minimum wage effects across the private and public sectors. This paper estimates the effects of the minimum wage on wages and employment in both the private and public sectors. The data used is an under-explored monthly Brazilian household survey from 1982 to 2000 at individual and regional levels. Robust results suggest that the minimum wage compresses the distribution of both sectors, but in line with a stronger effect in the private sector, more adverse employment effects in the long run are also observed in that sector. In the public sector, no evidence of adverse employment effects was uncovered.minimum wage; wage effect; employment effect; private sector; public sector; Brazil