A novel framework for predicting patients at risk of readmission

Uncertainty in decision-making for patients’ risk of re-admission arises due to non-uniform data and lack of knowledge in health system variables. The knowledge of the impact of risk factors will provide clinicians better decision-making and in reducing the number of patients admitted to the hospital. Traditional approaches are not capable to account for the uncertain nature of risk of hospital re-admissions. More problems arise due to large amount of uncertain information. Patients can be at high, medium or low risk of re-admission, and these strata have ill-defined boundaries. We believe that our model that adapts fuzzy regression method will start a novel approach to handle uncertain data, uncertain relationships between health system variables and the risk of re-admission. Because of nature of ill-defined boundaries of risk bands, this approach does allow the clinicians to target individuals at boundaries. Targeting individuals at boundaries and providing them proper care may provide some ability to move patients from high risk to low risk band. In developing this algorithm, we aimed to help potential users to assess the patients for various risk score thresholds and avoid readmission of high risk patients with proper interventions. A model for predicting patients at high risk of re-admission will enable interventions to be targeted before costs have been incurred and health status have deteriorated. A risk score cut off level would flag patients and result in net savings where intervention costs are much higher per patient. Preventing hospital re-admissions is important for patients, and our algorithm may also impact hospital income

Cambodia Report : Feeding China's Expanding Demand for Wood Pulp

After decades of war, Cambodia is one of the world's poorest nations, its economy and its political life are still suffering from the civil war that racked the country during the latter part of the 20th century. Rice and rubber were traditionally the principal exports of Cambodia, but exports fell sharply after the onset of the civil war, which put most of the rubber plantations out of operation. By the 1990s, however, rubber plantings had been undertaken as part of a national recovery program, and rubber and rice were again being exported. The fishing industry has also somehow been revived, but some food shortages continue. From this period, the largest source of export income has been timber, until the Cambodian government set up a “log export” ban in 1995. With a rather limited national environment supporting the development of an internationally competitive wood processing industry, this industry sector has not benefited from this ban. Wood material exports have continued under a limited processed form, i.e. squared logs and thick boards. Up to now, no development of any wood pulp or chipping industry has been impossible in Cambodia. Additionally, in 2002, any logging activity has been suspended for any forest companies, until the approval of their new forest concessions. Some forest companies which had old logs (harvested before 2001) were still authorized to process them. Further, in 2003, a large portion of the territory (about 24%) was declared as protected area. The industrial growth of the country is now mainly sustained by the garment and tourism sectors. But until now, inadequate transportation hampers the development of national industries, except in some “development pockets”. This poor transportation is a major impediment for the development of pulp wood plantations or pulp and chipping industries in Cambodia.forest; tropical forest; pulp; paper; economy; Cambodia; trade; network; globalisation; China

Rate-Equivocation Optimal Spatially Coupled LDPC Codes for the BEC Wiretap Channel

We consider transmission over a wiretap channel where both the main channel and the wiretapper's channel are Binary Erasure Channels (BEC). We use convolutional LDPC ensembles based on the coset encoding scheme. More precisely, we consider regular two edge type convolutional LDPC ensembles. We show that such a construction achieves the whole rate-equivocation region of the BEC wiretap channel. Convolutional LDPC ensemble were introduced by Felstr\"om and Zigangirov and are known to have excellent thresholds. Recently, Kudekar, Richardson, and Urbanke proved that the phenomenon of "Spatial Coupling" converts MAP threshold into BP threshold for transmission over the BEC. The phenomenon of spatial coupling has been observed to hold for general binary memoryless symmetric channels. Hence, we conjecture that our construction is a universal rate-equivocation achieving construction when the main channel and wiretapper's channel are binary memoryless symmetric channels, and the wiretapper's channel is degraded with respect to the main channel.Comment: Working pape

Finding Cures for Tropical Diseases: Is Open Source an Answer?

We construct polar codes for binary relay channels with orthogonal receiver components. We show that polar codes achieve the cut-set bound when the channels are symmetric and the relay-destination link supports compress-and-forward relaying based on Slepian-Wolf coding. More generally, we show that a particular version of the compress-and-forward rate is achievable using polar codes for Wyner-Ziv coding. In both cases the block error probability can be bounded as O(2-Nβ) for 0 &lt; β &lt; 1/2 and sufficiently large block length N.Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. QC 20111207</p