Learning with a Drifting Target Concept

We study the problem of learning in the presence of a drifting target concept. Specifically, we provide bounds on the error rate at a given time, given a learner with access to a history of independent samples labeled according to a target concept that can change on each round. One of our main contributions is a refinement of the best previous results for polynomial-time algorithms for the space of linear separators under a uniform distribution. We also provide general results for an algorithm capable of adapting to a variable rate of drift of the target concept. Some of the results also describe an active learning variant of this setting, and provide bounds on the number of queries for the labels of points in the sequence sufficient to obtain the stated bounds on the error rates

PyTAG: Challenges and Opportunities for Reinforcement Learning in Tabletop Games

In recent years, Game AI research has made important breakthroughs using Reinforcement Learning (RL). Despite this, RL for modern tabletop games has gained little to no attention, even when they offer a range of unique challenges compared to video games. To bridge this gap, we introduce PyTAG, a Python API for interacting with the Tabletop Games framework (TAG). TAG contains a growing set of more than 20 modern tabletop games, with a common API for AI agents. We present techniques for training RL agents in these games and introduce baseline results after training Proximal Policy Optimisation algorithms on a subset of games. Finally, we discuss the unique challenges complex modern tabletop games provide, now open to RL research through PyTAG

An enhanced static-list scheduling algorithm for temporal partitioning onto RPUs

This paper presents a novel algorithm for temporal partitioning of graphs representing a behavioral description. The algorithm is based on an extension of the traditional static-list scheduling that tailors it to resolve both scheduling and temporal partitioning. The nodes to be mapped into a partition are selected based on a statically computed cost model. The cost for each node integrates communication effects, the critical path length, and the possibility of the critical path to hide the delay of parallel nodes. In order to alleviate the runtime there is no dynamic update of the costs. A comparison of the algorithm to other schedulers and with close-to-optimum results obtained with a simulated annealing approach is shown. The presented algorithm has been implemented and the results show that it is robust, effective, and efficient, and when compared to other methods finds very good results in small amounts of CPU time

Repair Wind Field of Oil Spill Regional Using SAR Data

In this paper, we compared the normalized radar cross section (NRCS) of the synthetic aperture radar in the cases of oil spill and clean sea areas with image samples and determined their thresholds of the NRCS of SAR. we used the NRCS of clean water from the adjacent patches spill area to replace NRCS of oil spill area and retrieval wind field by CMOD5.N and comparison of wind velocity mending of oil spill with Model data the root mean square of wind speed and wind direction inversion are 0.89m/s and 20.26 satisfactory results, respectively. Therefore, after the occurrence not large scale oil spill, the real wind field could be restored by this method.&nbsp

Quantitative Modeling of Currents from a Voltage Gated Ion Channel Undergoing Fast Inactivation

Ion channels play a central role in setting gradients of ion concentration and electrostatic potentials, which in turn regulate sensory systems and other functions. Based on the structure of the open configuration of the Kv1.2 channel and the suggestion that the two ends of the N-terminal inactivating peptide form a bivalent complex that simultaneously blocks the channel pore and binds to the cytoplasmic T1 domain, we propose a six state kinetic model that for the first time reproduces the kinetics of recovery of the Drosophila Shaker over the full range of time scales and hyperpolarization potentials, including tail currents. The model is motivated by a normal mode analysis of the inactivated channel that suggests that a displacement consistent with models of the closed state propagates to the T1 domain via the S1-T1 linker. This motion stretches the bound (inactivating) peptide, hastening the unblocking of the pore. This pulling force is incorporated into the rates of the open to blocked states, capturing the fast recovery phase of the current for repolarization events shorter than 1 ms. If the membrane potential is hyperpolarized, essential dynamics further suggests that the T1 domain returns to a configuration where the peptide is unstretched and the S1-T1 linker is extended. Coupling this novel hyperpolarized substate to the closed, open and blocked pore states is enough to quantitatively estimate the number of open channels as a function of time and membrane potential. A straightforward prediction of the model is that a slow ramping of the potential leads to very small currents

XPD codon 312 and 751 polymorphisms, and AFB1 exposure, and hepatocellular carcinoma risk

<p>Abstract</p> <p>Background</p> <p>Genetic polymorphisms in DNA repair genes may influence individual variation in DNA repair capacity, which may be associated with risk of hepatocellular carcinoma (HCC) related to the exposure of aflatoxin B1 (AFB1). In this study, we have focused on the polymorphisms of xeroderma pigmentosum complementation group D (XPD) codon 312 and 751 (namely Asp312Asn and Lys751Gln), involved in nucleotide excision repair.</p> <p>Methods</p> <p>We conducted a case-control study including 618 HCC cases and 712 controls to evaluate the associations between these two polymorphisms and HCC risk for Guangxi population by means of TaqMan-PCR and PCR-RFLP analysis.</p> <p>Results</p> <p>We found that individuals featuring the XPD genotypes with codon 751 Gln alleles (namely XPD-LG or XPD-GG) were related to an elevated risk of HCC compared to those with the homozygote of XPD codon 751 Lys alleles [namely XPD-LL, adjusted odds ratios (ORs) were 1.75 and 2.47; 95% confidence interval (CIs) were 1.30-2.37 and 1.62-3.76, respectively]. A gender-specific role was evident that showed an higher risk for women (adjusted OR was 8.58 for XPD-GG) than for men (adjusted OR = 2.90 for XPD-GG). Interestingly, the interactive effects of this polymorphism and AFB1-exposure information showed the codon 751 Gln alleles increase the risk of HCC for individuals facing longer exposure years (<it>P</it>_interaction= 0.011, OR = 0.85). For example, long-exposure-years (> 48 years) individuals who carried XDP-GG had an adjusted OR of 470.25, whereas long-exposure-years people with XDP-LL were at lower risk (adjusted OR = 149.12). However, we did not find that XPD codon 312 polymorphism was significantly associated with HCC risk.</p> <p>Conclusion</p> <p>These findings suggest that XPD Lys751Gln polymorphism is an important modulator of AFB1 related-HCC development in Guangxi population.</p

Enzyme‐assisted aqueous extraction of Kalahari melon seed oil: optimization using response surface methodology

Enzymatic extraction of oil from Kalahari melon seeds was investigated and evaluated by response surface methodology (RSM). Two commercial protease enzyme products were used separately: Neutrase® 0.8 L and Flavourzyme® 1000 L from Novozymes (Bagsvaerd, Denmark). RSM was applied to model and optimize the reaction conditions namely concentration of enzyme (20–50 g kg−1 of seed mass), initial pH of mixture (pH 5–9), incubation temperature (40–60 °C), and incubation time (12–36 h). Well fitting models were successfully established for both enzymes: Neutrase 0.8 L (R 2 = 0.9410) and Flavourzyme 1000 L (R 2 = 0.9574) through multiple linear regressions with backward elimination. Incubation time was the most significant reaction factor on oil yield for both enzymes. The optimal conditions for Neutrase 0.8 L were: an enzyme concentration of 25 g kg−1, an initial pH of 7, a temperature at 58 °C and an incubation time of 31 h with constant shaking at 100 rpm. Centrifuging the mixture at 8,000g for 20 min separated the oil with a recovery of 68.58 ± 3.39%. The optimal conditions for Flavourzyme 1000 L were enzyme concentration of 21 g kg−1, initial pH of 6, temperature at 50 °C and incubation time of 36 h. These optimum conditions yielded a 71.55 ± 1.28% oil recovery