A specialized inventory problem in banks: optimizing retail sweeps

Deposits held at Federal Reserve Banks are an essential input to the business activity of most depository institutions in the United States. Managing these deposits is an important and complex inventory problem, for two reasons. First, Federal Reserve regulations require that depository institutions hold certain amounts of such deposits at the Federal Reserve Banks to satisfy statutory reserve requirements against customers* transaction accounts (demand deposits and other checkable deposits). Second, some inventory of such deposits is essential for banks to operate one of their core lines of business: furnishing payment services to households and firms. including wire transfers, ACH payments, and check clearing settlement. Because the Federal Reserve does not pay interest on such deposits used to satisfy statutory reserve requirements, banks seek to minimize their inventory of such deposits. In 1994, the banking industry introduced a new inventory management tool for such deposits, the retail deposit sweep program, which avoids the statutory requirement by reclassifying transaction deposits as savings deposits. In this analysis, we examine two algorithms for operating such sweeps programs within the limits of Federal Reserve regulations.Banks and banking ; Retail trade

Moderators and predictors of response to cognitive behaviour therapy for pediatric obsessive-compulsive disorder: A systematic review

We report a systematic review of moderators of CBT efficacy for pediatric OCD relative to other treatments. CENTRAL, MEDLINE, EMBASE, CINAHL, and PsycINFO were searched for RCTs reporting on effect moderation for CBT outcomes. Five studies (N = 365) examined 17 variables with three significant moderators identified. Compared to pill-placebo, CBT monotherapy was not effective for children with a family history of OCD but was for those without a family history. For children with a family history, CBT plus sertraline efficacy was attenuated but remained significant. For children with tics, CBT but not sertraline remained superior to pill-placebo. For non-responders to initial treatment with CBT, continuing CBT was inferior to commencing sertraline for those with tics but was not different for those without tics. A supplementary review identified older age, symptom and impairment severity, co-morbidity and family accommodation as consistent predictors of a poorer outcome to CBT. Current evidence for moderation effects is post-hoc, from single RCTs, has small Ns and requires replication. The review identifies family history of OCD and the presence of tics as factors requiring further examination in properly conducted trials and about which clinicians need to show care in their treatment recommendations

Converting Treatment Plans From Helical Tomotherapy to L-Shape Linac: Clinical Workflow and Dosimetric Evaluation.

This work evaluated a commercial fallback planning workflow designed to provide cross-platform treatment planning and delivery. A total of 27 helical tomotherapy intensity-modulated radiotherapy plans covering 4 anatomical sites were selected, including 7 brain, 5 unilateral head and neck, 5 bilateral head and neck, 5 pelvis, and 5 prostate cases. All helical tomotherapy plans were converted to 7-field/9-field intensity-modulated radiotherapy and volumetric-modulated radiotherapy plans through fallback dose-mimicking algorithm using a 6-MV beam model. The planning target volume (PTV) coverage ( D1, D99, and homogeneity index) and organs at risk dose constraints were evaluated and compared. Overall, all 3 techniques resulted in relatively inferior target dose coverage compared to helical tomotherapy plans, with higher homogeneity index and maximum dose. The organs at risk dose ratio of fallback to helical tomotherapy plans covered a wide spectrum, from 0.87 to 1.11 on average for all sites, with fallback plans being superior for brain, pelvis, and prostate sites. The quality of fallback plans depends on the delivery technique, field numbers, and angles, as well as user selection of structures for organs at risk. In actual clinical scenario, fallback plans would typically be needed for 1 to 5 fractions of a treatment course in the event of machine breakdown. Our results suggested that <1% dose variance can be introduced in target coverage and/or organs at risk from fallback plans. The presented clinical workflow showed that the fallback plan generation typically takes 10 to 20 minutes per case. Fallback planning provides an expeditious and effective strategy for transferring patients cross platforms, and minimizing the untold risk of a patient missing treatment(s)

A Genetic Programming Approach to Designing Convolutional Neural Network Architectures

The convolutional neural network (CNN), which is one of the deep learning models, has seen much success in a variety of computer vision tasks. However, designing CNN architectures still requires expert knowledge and a lot of trial and error. In this paper, we attempt to automatically construct CNN architectures for an image classification task based on Cartesian genetic programming (CGP). In our method, we adopt highly functional modules, such as convolutional blocks and tensor concatenation, as the node functions in CGP. The CNN structure and connectivity represented by the CGP encoding method are optimized to maximize the validation accuracy. To evaluate the proposed method, we constructed a CNN architecture for the image classification task with the CIFAR-10 dataset. The experimental result shows that the proposed method can be used to automatically find the competitive CNN architecture compared with state-of-the-art models.Comment: This is the revised version of the GECCO 2017 paper. The code of our method is available at https://github.com/sg-nm/cgp-cn

Intercontinental spread of pyrimethamine-resistant malaria.

Here we present molecular evidence demonstrating that malaria parasites bearing high-level pyrimethamine resistance originally arrived in Africa from southeast Asia. The resistance alleles carried by these migrants are now spreading across Africa at an alarming rate, signaling the end of affordable malaria treatment and presenting sub-Saharan Africa with a public health crisis

Using stable isotopes to investigate interactions between the forest carbon and nitrogen cycles

Nitrogen (N) fertilization due to atmospheric deposition (NDEP ) may explain some of the net carbon (C) sink (0.6-0.7 Pg y-1) in temperate forests, but estimates of the additional C uptake due to atmospheric N additions (∆C/∆N) can vary by over an order of magnitude (5 to 200 ∆C/∆N). High estimates from several recent studies [e.g. Magnani (2007), Nature 447 848-850], deriving ∆C/∆N from regional correlations between NDEP and measures of C uptake (such as eddy covariance -derived net ecosystem production, or forest inventory data) contradict estimates from other studies, particularly those involving 15N tracer applications added as fertilizer to the forest floor. A strong ∆C/∆N effect requires nitrogen to be efficiently acquired by trees and allocated to high C:N, long-lived woody tissues, but these isotope experiments typically report relatively little (~ 20 %) of 15N added is found above-ground, with less than 5 % of the total 15N applied found in wood. Consequently the high correlation-derived ∆C/∆N estimates are often attributed to co-variation with other factors across the range of sites investigated. However, 15N-fertilization treatments often impose considerably higher total N loads than ambient NDEP , while almost all exclusively only apply mineral 15N treatments to the soil, often in a limited number of treatment events over relatively short periods of time. Excessive N deposition loads can induce negative physiological effects and limit the resulting ∆C/∆N observed, and applying treatments to the soil ignores canopy nitrogen uptake, which has been demonstrated in numerous studies. As canopies can directly take up nitrogen, the chronic, (relatively) low levels of ambient NDEP inputs from pollution may be acquired without some of the effects of heavy N loads, with trees obtaining this N before it reaches the soil, allowing canopies to substitute for, or supplement, edaphic N nutrition. The strength of this effect depends on how much N uptake can occur across the canopy under field conditions, and if this extra N supplies growth in woody tissues such as the stem, as well as the canopy. Similarly, such mineral fertilizer isotope trace experiments are also unable to trace N in the decomposing litter and humus layers of the soil, which even under heavy NDEP loading contribute most of the N utilised for forest growth. Recent literature suggests that some organic (early decomposition) forms of N may be taken up by roots. If this litter N is not retained or distributed in the same way as mineral fertilizers, its contribution to plant nutrition and ∆C/∆N may need to be reassessed under nitrogen deposition. We tested some of these assumptions in the nursery and the field. In order to facilitate litter 15N tracing, we conducted an experiment injecting large trees with 15N-NH4NO3 to create 15N-labelled litter, tracing the applied isotope into a full harvest of the canopy. Such labelled litter substitute was used to replace the litter layer in a Sitka Spruce plantation (Picea sitchensis L. (Bong.)), where the fate of this 15N from litter decomposition in the soil system was compared against the fate of 15N in deposition. Similarly, in potted Sitka Spruce saplings, we used combination treatments of 15N-labelled litter, soil-targeted 15N-deposition, and canopy targeted 15N-deposition, investigating 15N return in different age classes of above and below ground biomass. We found that i) 15N recovery in canopies (needles and branches) in our injected trees was almost all of the injected 15N five months after injection, ii) canopy application of NDEP led to 60 % 15N return in above-ground parts of saplings compared to 21 % in soil applications and iii) a litter-derived 15N source was retained 55 % more in topsoil, and 36 % more in roots, than a similar deposition 15N source applied as mineral fertilizer. We discuss the implications of such findings in the context of 15N return in different plant organs and ecosystem pools, seasonal variation in N content, and overall inferences of a forest ∆C/∆N effect. Our results suggest that the total ∆C/∆N effect driven by a high N sequestration from canopy uptake in wood is ~ 114:1, more than double that of 15N tracer experiments but not as high as upper estimates from correlative studies, and that litter-derived organic N is better retained in trees and soils in excess of similar amounts of mineral 15N from deposition. Existing forest 15N-fertilization experiments could under-estimate the overall ∆C/∆N effect of atmospheric N deposition

TransNets: Learning to Transform for Recommendation

Recently, deep learning methods have been shown to improve the performance of recommender systems over traditional methods, especially when review text is available. For example, a recent model, DeepCoNN, uses neural nets to learn one latent representation for the text of all reviews written by a target user, and a second latent representation for the text of all reviews for a target item, and then combines these latent representations to obtain state-of-the-art performance on recommendation tasks. We show that (unsurprisingly) much of the predictive value of review text comes from reviews of the target user for the target item. We then introduce a way in which this information can be used in recommendation, even when the target user's review for the target item is not available. Our model, called TransNets, extends the DeepCoNN model by introducing an additional latent layer representing the target user-target item pair. We then regularize this layer, at training time, to be similar to another latent representation of the target user's review of the target item. We show that TransNets and extensions of it improve substantially over the previous state-of-the-art.Comment: Accepted for publication in the 11th ACM Conference on Recommender Systems (RecSys 2017