Unbounded Human Learning: Optimal Scheduling for Spaced Repetition

In the study of human learning, there is broad evidence that our ability to retain information improves with repeated exposure and decays with delay since last exposure. This plays a crucial role in the design of educational software, leading to a trade-off between teaching new material and reviewing what has already been taught. A common way to balance this trade-off is spaced repetition, which uses periodic review of content to improve long-term retention. Though spaced repetition is widely used in practice, e.g., in electronic flashcard software, there is little formal understanding of the design of these systems. Our paper addresses this gap in three ways. First, we mine log data from spaced repetition software to establish the functional dependence of retention on reinforcement and delay. Second, we use this memory model to develop a stochastic model for spaced repetition systems. We propose a queueing network model of the Leitner system for reviewing flashcards, along with a heuristic approximation that admits a tractable optimization problem for review scheduling. Finally, we empirically evaluate our queueing model through a Mechanical Turk experiment, verifying a key qualitative prediction of our model: the existence of a sharp phase transition in learning outcomes upon increasing the rate of new item introductions.Comment: Accepted to the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 201

The potential impact of CT-MRI matching on tumor volume delineation in advanced head and neck cancer

To study the potential impact of the combined use of CT and MRI scans on the Gross Tumor Volume (GTV) estimation and interobserver variation. Four observers outlined the GTV in six patients with advanced head and neck cancer on CT, axial MRI, and coronal or sagittal MRI. The MRI scans were subsequently matched to the CT scan. The interobserver and interscan set variation were assessed in three dimensions. The mean CT derived volume was a factor of 1.3 larger than the mean axial MRI volume. The range in volumes was larger for the CT than for the axial MRI volumes in five of the six cases. The ratio of the scan set common (i.e., the volume common to all GTVs) and the scan set encompassing volume (i.e., the smallest volume encompassing all GTVs) was closer to one in MRI (0.3-0.6) than in CT (0.1-0.5). The rest volumes (i.e., the volume defined by one observer as GTV in one data set but not in the other data set) were never zero for CT vs. MRI nor for MRI vs. CT. In two cases the craniocaudal border was poorly recognized on the axial MRI but could be delineated with a good agreement between the observers in the coronal/sagittal MRI. MRI-derived GTVs are smaller and have less interobserver variation than CT-derived GTVs. CT and MRI are complementary in delineating the GTV. A coronal or sagittal MRI adds to a better GTV definition in the craniocaudal directio

Giant Taro (Alocasia macrorrhiza) Root Meal with or without Coconut Oil Slurry as Source of Dietary Energy for Laying Hens

The effect of feeding Alocasia macrorrhiza root meal (AMRM) with or without added coconut oil slurry (COS) on egg production and egg qualities was investigated in a 20-week experiment. A control diet based on maize and 4 other diets containing 10 and 20% AMRM with or without COS were fed each to 4 replicates of 10 birds in a completely randomized design. There were no significant dietary effects on feed intake (FI) and the intake of lysine, methionine and metabolizable energy (ME). Birds fed the 20% AMRM_COS added significantly less weight during the experimental period compared to the control fed group. Body weight change (BWC) did not differ among the AMRM fed birds. Per cent hen-day and feed conversion ratio were depressed on 20% AMRM and egg weight on 10% AMRM but these depressing effects were overcome by COS addition. Egg shape index, Haugh unit and per cent shell were not affected by the diet. It is concluded that AMRM can replace 10% dietary maize without adverse effect on laying performance but 20% replacement negatively impacts on hen-day and egg weight. These adverse effects are however, overcome by treating AMRM with COS at the ratio of 9: 1. More research into higher levels of COS treated AMRM in the diet is warranted

Do biomass burning aerosols intensify drought in equatorial Asia during El Niño?

During El Niño years, fires in tropical forests and peatlands in equatorial Asia create large regional smoke clouds. We characterized the sensitivity of these clouds to regional drought, and we investigated their effects on climate by using an atmospheric general circulation model. Satellite observations during 2000–2006 indicated that El Niño-induced regional drought led to increases in fire emissions and, consequently, increases in aerosol optical depths over Sumatra, Borneo and the surrounding ocean. Next, we used the Community Atmosphere Model (CAM) to investigate how climate responded to this forcing. We conducted two 30 year simulations in which monthly fire emissions were prescribed for either a high (El Niño, 1997) or low (La Niña, 2000) fire year using a satellite-derived time series of fire emissions. Our simulations included the direct and semi-direct effects of aerosols on the radiation budget within the model. We assessed the radiative and climate effects of anthropogenic fire by analyzing the differences between the high and low fire simulations. Fire aerosols reduced net shortwave radiation at the surface during August–October by 19.1±12.9 W m<sup>−2</sup> (10%) in a region that encompassed most of Sumatra and Borneo (90° E–120° E, 5° S–5° N). The reductions in net shortwave radiation cooled sea surface temperatures (SSTs) and land surface temperatures by 0.5±0.3 and 0.4±0.2 °C during these months. Tropospheric heating from black carbon (BC) absorption averaged 20.5±9.3 W m<sup>−2</sup> and was balanced by a reduction in latent heating. The combination of decreased SSTs and increased atmospheric heating reduced regional precipitation by 0.9±0.6 mm d<sup>−1</sup> (10%). The vulnerability of ecosystems to fire was enhanced because the decreases in precipitation exceeded those for evapotranspiration. Together, the satellite and modeling results imply a possible positive feedback loop in which anthropogenic burning in the region intensifies drought stress during El Niño

Finite-Element Discretization of Static Hamilton-Jacobi Equations Based on a Local Variational Principle

We propose a linear finite-element discretization of Dirichlet problems for static Hamilton-Jacobi equations on unstructured triangulations. The discretization is based on simplified localized Dirichlet problems that are solved by a local variational principle. It generalizes several approaches known in the literature and allows for a simple and transparent convergence theory. In this paper the resulting system of nonlinear equations is solved by an adaptive Gauss-Seidel iteration that is easily implemented and quite effective as a couple of numerical experiments show.Comment: 19 page

Kappa free light chain index as a diagnostic biomarker in multiple sclerosis: a real-world investigation

Kappa free light chain (KFLC)-index, a measure for intrathecal production of free kappa chains, has been increasingly recognized for its diagnostic potential in multiple sclerosis (MS) as a quantitative alternative to IgG oligoclonal-bands (OCBs). Our objective was to investigate the sensitivity, specificity, and overall diagnostic accuracy of KFLC-index in MS. KFLC-index was prospectively determined as part of the diagnostic workup in patients with suspected MS (n=327) between May 2013 and February 2020. Patients with clinically isolated syndrome (CIS), radiologically isolated syndrome (RIS), and MS had markedly higher KFLC-index (44.6, IQR 16-128) compared with subjects with other neuro-inflammatory disorders (ONID) and symptomatic controls (SC) (2.19, IQR 1.68-2.98, pIF and better than for IgG-index. We show that KFLC-index was influenced neither by DMT, nor by demographic factors or other inflammatory or degenerative processes in MS as determined by biomarkers in CSF

Using item response theory to explore the psychometric properties of extended matching questions examination in undergraduate medical education

BACKGROUND: As assessment has been shown to direct learning, it is critical that the examinations developed to test clinical competence in medical undergraduates are valid and reliable. The use of extended matching questions (EMQ) has been advocated to overcome some of the criticisms of using multiple-choice questions to test factual and applied knowledge. METHODS: We analysed the results from the Extended Matching Questions Examination taken by 4th year undergraduate medical students in the academic year 2001 to 2002. Rasch analysis was used to examine whether the set of questions used in the examination mapped on to a unidimensional scale, the degree of difficulty of questions within and between the various medical and surgical specialties and the pattern of responses within individual questions to assess the impact of the distractor options. RESULTS: Analysis of a subset of items and of the full examination demonstrated internal construct validity and the absence of bias on the majority of questions. Three main patterns of response selection were identified. CONCLUSION: Modern psychometric methods based upon the work of Rasch provide a useful approach to the calibration and analysis of EMQ undergraduate medical assessments. The approach allows for a formal test of the unidimensionality of the questions and thus the validity of the summed score. Given the metric calibration which follows fit to the model, it also allows for the establishment of items banks to facilitate continuity and equity in exam standards

Statistical Inference in a Directed Network Model with Covariates

Networks are often characterized by node heterogeneity for which nodes exhibit different degrees of interaction and link homophily for which nodes sharing common features tend to associate with each other. In this paper, we propose a new directed network model to capture the former via node-specific parametrization and the latter by incorporating covariates. In particular, this model quantifies the extent of heterogeneity in terms of outgoingness and incomingness of each node by different parameters, thus allowing the number of heterogeneity parameters to be twice the number of nodes. We study the maximum likelihood estimation of the model and establish the uniform consistency and asymptotic normality of the resulting estimators. Numerical studies demonstrate our theoretical findings and a data analysis confirms the usefulness of our model.Comment: 29 pages. minor revisio

Rigorous mean-field dynamics of lattice bosons: Quenches from the Mott insulator

We provide a rigorous derivation of Gutzwiller mean-field dynamics for lattice bosons, showing that it is exact on fully connected lattices. We apply this formalism to quenches in the interaction parameter from the Mott insulator to the superfluid state. Although within mean-field the Mott insulator is a steady state, we show that a dynamical critical interaction $U_d$ exists, such that for final interaction parameter $U_f>U_d$ the Mott insulator is exponentially unstable towards emerging long-range superfluid order, whereas for $U_f<U_d$ the Mott insulating state is stable. We discuss the implications of this prediction for finite-dimensional systems.Comment: 6 pages, 3 figures, published versio